Speech Compression

In this paper we present a technique of efficacy improvement of speech signal compression algorithm without individual features speech production loss. The compression in this case means to delete, from the digital signal, those quantization steps that can be predi cted. We propose to decrease the number of those quantization steps using a modified linear predication algorithm w ith variable order. That allows to decrease compression time and save computer resource.

The paper gives the details about the speech compression using discrete wavelet transform in FPGA. In today's world multimedia files are used, storage space required for these files is more and sound files have no option so ultimate solution for this is compression. Compression is nothing but high input stream of data converted into smaller size. Compression is done for all, such as image, data; signals. Here speech compression technique is used and done using DWT. For this purpose only single level implementation is done to get compressed signal, and this is implemented in FPGA by using VHDL code. In this technique DWT code is written in VHDL that include separation of high level component and low level component from given input wav file and after separating these components down sampling is done and we get the compressed speech signal by keeping only approximation part of the result. The compressed speech signal was read back after up-sampling was performed. The resulting compressed signal is with some noise and future work is to reduce noise.

Voice over Internet Protocol (VoIP) is a revolutionary technology which is acting as a platform for the development of latest trends in modern communication world. The speech signal quality in VoIP is governed by the speech coding techniques employed. Currently various standard coders like FS-1015(LPC-10), ITU-G.711, ITU-G.726, FS-1016(ITU-G.728), etc. are used to digitize the speech signal. Modern research trends in signal processing are concentrating on the wavelet based compression techniques. This paper analyzes the performance of the standard codecs with various wavelet based codecs by statistical analysis of the coding capabilities of the codecs for English and Hindi language sentences spoken by a male and a female speaker. The performance is measured in terms of Compression Ratio (CR), Signal to Noise Ratio (SNR), Normalized Root Mean Square Error (NRSME) and Mean Opinion Score (MOS)

Speech processing is the fastest growing technology due to its applications in various fields such as research, forensic and aid for blind people. This paper describes speech processing techniques which involve improving the signal to noise ratio, reducing the compression rate and decreasing the bandwidth required for transmission involving minimum error in the signal at the receiver end. The speech compression and compressed sensing is done using MP3 technique which is basically compression and decompression using DCT-IDCT technique as well as a comparative study between compressed sensing and compression of speech signals based on Word Error Rate (WER), Peak Signal to Noise Ratio (PSNR), Mean Square Error (MSE) and Compression Ratio using MATLAB R2009a as software.

Database security is the mechanisms that secure the database against deliberate or accidental threats, unauthorized users, hackers and ip snoopers. In this paper we proposed two mixed techniques to secure the database ie one is authentication followed by cryptography of database. In existing system the algorithm is less secure, less complex and much superior to implement in any system. The encryption algorithm is built on genetic algorithm, it is used to encrypt the database and validate the user’s login id and password, it must verify the user and allow the user to access the database. The decryption also has a login and password based on decryption algorithm and genetic algorithm. The database used is SQL Server 2003. This paper researches and analyzes the issues of security and defense. Keywords:- Network database, cryptography, genetic algorithm, encryption and decryption I.

In the applications of Internet and wireless communication network, information security is one of the most challenging aspects. Cryptography is the best solution that offers the requisite protection from unintended persons. By using encryption and decryption mechanisms, cryptography can convert the data form its readable form to unreadable one so that only the intended receiver can read the message and alter it. By this way, one can ensure that message can be sent or stored without any modification. The presented work is concerned with a particular type of asymmetric key cryptography called El-Gamal algorithm to be used for speech signals encryption and decryption. First, the speech signal is encrypted by employing El-Gamal algorithm throughout encryption process at the sender and then transmitted to the particular recipient. Second, the recipient will recover the original signal throughout the decryption process. The cryptosystem performance is evaluated via different quality measures for audio signals encryption/decryption including Signal to Noise Ratio, Segmental Signal to Noise-Ratio and Log-Likelihood Ratio that are reach to-35.0224 dB,-38.0201 dB and 2.1145 respectively for the encrypted signal. The given results confirm the effectiveness of the presented scheme and robustness against noise effect.

Image restoration forms the foundation of various applications in the areas of medicine, astronomy etc. Historically an image is reproduced utilizing numerous techniques of which Fourier and wavelet transform systems developed from the sources of present-day technologies. The rebuilding images own higher purpose and help in interpreting the image in extra detail. A wavelet is a wave-like oscillation with amplitude which begins from zero, progress, and then decreases over to zero. In numerical analysis and functional analysis, a discrete wavelet transform (DWT) systems is any wavelet change for which the wavelets have discretely experimented. As with additional wavelet transforms, a key success it has higher Fourier transforms is a transient resolution: it catches both frequencies as well as location information.

There is a fast growing need to support audio voice communication in wireless channel between a voice source and personal computer PC. In this paper we develop an algorithm using matlab software to indicate how a PC can receive audio voice signal from an audio source, record it and plot the resulting waveform on a graphical representation. The actual data rate for audio voice transmission over IP is 64000bps, which was used as medium for audio voice communication between a PC and audio voice source. 
Keywords: Audio Voice, Personal Computer (PC), Algorithm, Data Rate

This article introduces a new technique for voice signals encryption & decryption to ameliorate the information security during transferring over unsecure network. The presented mechanism is based on a particular type of asymmetric key cryptography called Diffie-Hellman Algorithm. The main reason of using this algorithm is enabling users to encrypt and decrypt their messages via a shared session key that is known only for them. Firstly, the input voice signal in this scheme is enciphered by utilizing the shared secret key at the dispatcher. Secondly, the scrambled voice signal is delivered to the destination through open telecommunication network. Eventually, the cipher text signal is deciphered at the receptor by exploiting the same key to retrieve the plaintext signal. The performance of the presented voice cryptosystem is assessed via different known ciphering/deciphering voice measures for different voice signals. The computed and visual results in addition to comparison outcome...

In the applications of Internet and wireless communication network, information security is one of the most challenging aspects. Cryptography is the best solution that offers the requisite protection from unintended persons. By using encryption and decryption mechanisms, cryptography can convert the data form its readable form to unreadable one so that only the intended receiver can read the message and alter it. By this way, one can ensure that message can be sent or stored without any modification. The presented work is concerned with a particular type of asymmetric key cryptography called El-Gamal algorithm to be used for speech signals encryption and decryption. First, the speech signal is encrypted by employing El-Gamal algorithm throughout encryption process at the sender and then transmitted to the particular recipient. Second, the recipient will recover the original signal throughout the decryption process. The cryptosystem performance is evaluated via different quality measures for audio signals encryption/decryption including Signal to Noise Ratio, Segmental Signal to Noise-Ratio and Log-Likelihood Ratio that are reach to-35.0224 dB,-38.0201 dB and 2.1145 respectively for the encrypted signal. The given results confirm the effectiveness of the presented scheme and robustness against noise effect.

In this paper, we studied the effects of voice codecs on remote speaker recognition system, considering three types of speech codec: PCM, DPCM and ADPCM conforming to International Telecommunications Union Telecoms (ITU-T) recommendation used in telephony and VoIP (Voice over Internet Protocol). To improve the performance of speaker recognition in a noisy environment, we propose a new speech activity detection algorithm (SAD) using ''Adaptive Threshold'', which can be simulated with speech wave files of TIMIT (Texas Instruments Massachusetts Institute of Technology) database that allows recognition system to be done under almost ideal conditions. Moreover, the speaker recognition system is based on Vector Quantization as speaker modeling technique and Mel Frequency Cepstral Coefficient (MFCC) as feature extraction technique. Where, the feature extraction proceed after (for testing phase) and before (for training phase) the speech is sending over communication channel...

Large-scale mobile communication systems tend to contain legacy transmission channels with narrowband bottlenecks, resulting in characteristic 'telephone-quality' audio. While higher quality codecs exist, due to the scale and heterogeneity of the networks, transmitting higher sample rate audio with modern high-quality audio codecs can be difficult in practice. This paper proposes an approach where a communication node can instead extend the bandwidth of a band-limited incoming speech signal that may have been passed through a low-rate codec. To this end, we propose a WaveNet-based model conditioned on a log-mel spectrogram representation of a bandwidth-constrained speech audio signal of 8 kHz and audio with artifacts from GSM full-rate (FR) compression to reconstruct the higher-resolution signal. In our experimental MUSHRA evaluation, we show that a model trained to upsample to 24kHz speech signals from audio passed through the 8kHz GSM-FR codec is able to reconstruct audio only slightly lower in quality to that of the Adaptive Multi-Rate Wideband audio codec (AMR-WB) codec at 16kHz, and closes around half the gap in perceptual quality between the original encoded signal and the original speech sampled at 24kHz. We further show that when the same model is passed 8kHz audio that has not been compressed, is able to again reconstruct audio of slightly better quality than 16kHz AMR-WB, in the same MUSHRA evaluation.

Today in the age of technology the use of digital visual system increasing at tremendous rate for information entertainment and education purpose therefore it has become essential to reduce the cost of image transmission and storage as this application have become increasingly importance we give attention towards image compression major objective of image compression is to represent the image as few bit as possible while preserving level of quality and intelligibility regards for given application. Wavelet based image compression provides substantial improvement in picture quality at higher compression ratio. Over the past few years a variety of powerful and sophisticated wavelet based scheme for image compression have been developed and implemented. Because of the many advantages in the upcoming jpeg-2000 standard are all wavelet based compression algorithms. Discrete wavelet transforms is the most popular transformation technique adopted for image compression. Complexity of DWT is...

The advancement of systems with the capacity to compress audio signals and simultaneously secure is a highly attractive research subject. This is because of the need to enhance storage usage and speed up the transmission of data, as well as securing the transmission of sensitive signals over limited and insecure communication channels. Thus, many researchers have studied and produced different systems, either to compress or encrypt audio data using different algorithms and methods, all of which suffer from certain issues including high time consumption or complex calculations. This paper proposes a compressing sensing-based system that compresses audio signals and simultaneously provides an encryption system. The audio signal is segmented into small matrices of samples and then multiplied by a non-square sensing matrix generated by a Gaussian random generator. The reconstruction process is carried out by solving a linear system using the pseudoinverse of Moore-Penrose. The statistic...

The advancement of systems with the capacity to compress audio signals and simultaneously secure is a highly attractive research subject. This is because of the need to enhance storage usage and speed up the transmission of data, as well as securing the transmission of sensitive signals over limited and insecure communication channels. Thus, many researchers have studied and produced different systems, either to compress or encrypt audio data using different algorithms and methods, all of which suffer from certain issues including high time consumption or complex calculations. This paper proposes a compressing sensing-based system that compresses audio signals and simultaneously provides an encryption system. The audio signal is segmented into small matrices of samples and then multiplied by a non-square sensing matrix generated by a Gaussian random generator. The reconstruction process is carried out by solving a linear system using the pseudoinverse of Moore-Penrose. The statistical analysis results obtaining from implementing different types and sizes of audio signals prove that the proposed system succeeds in compressing the audio signals with a ratio reaching 28% of real size and reconstructing the signal with a correlation metric between 0.98 and 0.99. It also scores very good results in the normalized mean square error (MSE), peak signal-to-noise ratio metrics (PSNR), and the structural similarity index (SSIM), as well as giving the signal a high level of security.

In this paper an audio coding scheme based on the Empirical Mode Decomposition (EMD) in association with the Hilbert transform is presented. The audio signal is decomposed adaptively into intrinsic oscillatory components by EMD called Intrinsic Mode Functions (IMFs) and the associated instantaneous amplitudes and the instantaneous phases calculated. The basic principle of the proposed approach consists in encoding the instantaneous amplitudes and the instantaneous phases. The decoder recovers the original signal after IMFs reconstruction by demodulation, and their summation. The compression method is applied to different audio signals, and results compared to MP3 and to wavelet approaches.

Global System for Mobile Communications (GSM) is one of the most commonly used cellular technologies in the world. One of the objectives in mobile communication systems is the security of the exchanged data. GSM employs many cryptographic algorithms for security like A5/1, A5/2 and A5/3. Even so, these algorithms do not provide sufficient level of security for protecting the confidentiality of GSM. Therefore, it is desirable to increase security by additional encryption methods. This paper presents a voice encryption method called: “RSA with Random permutation and Inversion”, based on current voice channel, which overcomes data channel's insufficiencies and solves the problem of penetrating the RPE-LTP vocoder by the encrypted voice. The proposed method fulfils an end-to-end secured communication in the GSM; insure a good compatibility to all GSM networks, and easy implementation without any modification in these systems.

The performance of audio steganography compression system using discrete wavelet transform (DWT) is investigated. Audio steganography coding is the technology of transforming stegospeech into efficiently encoded version that can be decoded in the receiver side to produce a close representation of the initial signal (non compressed). Experimental results prove the efficiency of the used compression technique since the compressed stego-speech are perceptually intelligible and indistinguishable from the equivalent initial signal, while being able to recover the initial stego-speech with slight degradation in the quality .

In this paper, we studied the effects of voice codecs on remote speaker recognition system, considering three types of speech codec: PCM, DPCM and ADPCM conforming to International Telecommunications Union Telecoms (ITU-T) recommendation used in telephony and VoIP (Voice over Internet Protocol). To improve the performance of speaker recognition in a noisy environment, we propose a new speech activity detection algorithm (SAD) using ''Adaptive Threshold'', which can be simulated with speech wave files of TIMIT (Texas Instruments Massachusetts Institute of Technology) database that allows recognition system to be done under almost ideal conditions. Moreover, the speaker recognition system is based on Vector Quantization as speaker modeling technique and Mel Frequency Cepstral Coefficient (MFCC) as feature extraction technique. Where, the feature extraction proceed after (for testing phase) and before (for training phase) the speech is sending over communication channel...

One of the biggest problems in cryptography is the distribution of keys. Suppose you live in the United States and want to pass information secretly to your friend in Europe. If you truly want to keep the information secret, you need to agree on some sort of key that you and he can use to encode/decode messages. But you don't want to keep using the same key, or you will make it easier and easier for others to crack your cipher. But it's also a pain to get keys to your friend. If you mail them, they might be stolen. If you send them cryptographically, and someone has broken your code, that person will also have the next key. If you have to go to Europe regularly to hand-deliver the next key, that is also expensive. If you hire some courier to deliver the new key, you have to trust the courier, et cetera. One solution is provided by digital signature as digital signatures are used to detect unauthorized modifications to data and to authenticate the identity of the signatory. B...

The advancement of systems with the capacity to compress audio signals and simultaneously secure is a highly attractive research subject. This is because of the need to enhance storage usage and speed up the transmission of data, as well as securing the transmission of sensitive signals over limited and insecure communication channels. Thus, many researchers have studied and produced different systems, either to compress or encrypt audio data using different algorithms and methods, all of which suffer from certain issues including high time consumption or complex calculations. This paper proposes a compressing sensing-based system that compresses audio signals and simultaneously provides an encryption system. The audio signal is segmented into small matrices of samples and then multiplied by a non-square sensing matrix generated by a Gaussian random generator. The reconstruction process is carried out by solving a linear system using the pseudoinverse of Moore-Penrose. The statistical analysis results obtaining from implementing different types and sizes of audio signals prove that the proposed system succeeds in compressing the audio signals with a ratio reaching 28% of real size and reconstructing the signal with a correlation metric between 0.98 and 0.99. It also scores very good results in the normalized mean square error (MSE), peak signal-to-noise ratio metrics (PSNR), and the structural similarity index (SSIM), as well as giving the signal a high level of security.

Abstract--The aim of the Paper is to provide the security during transmission of the data. Commonly used technologies are cryptography, Compression and decompression. This can be used for secure and fast sending for security purpose we are using the Cryptography ...

In this paper, a system for the purpose of signals encryption using the technique of independent component analysis has been proposed. The proposed system mixes the original signal with arbitrary number of random signals in order to obtain a highly encrypted signal like noise. The number of random signals is indicated by an attached key signal preceding the encrypted signal. In order to increase the encryption strength, the number of random signals is changed at each signal transmission. An independent component analysis technique is utilized to separate signals and select the original signal by a designed selector. A set of parameters has been adopted to measure the encryption quality and decryption capability. Promising encryption results represented by up to-48.35 dB for segmental spectral signal to noise ratio and 0.00037 correlation coefficient between the original and the encrypted signals are obtained. As well, an efficient signal decryption is achieved with 45.85 dB signal to noise ratio and nearly 1 correlation coefficient value between the original and reconstructed signals. In conclusion, the proposed system is a good candidate to be adopted in developing highly reliable security transceiver systems.

This paper presents a technique for image compression and hiding in image of a high secret has been applied to wavelet transform and wavelet transform packet first apply two dimensional wavelet transform packet on the cover image was analysis and resorting to (Secret Sub bands level) of the cover image has secret algorithm either the image you want to hide has been compressed using two dimensional wavelet transform and then the application (Hard Thresholding) in order to reduce the values of the image and was also resorting to the transactions analysis (Secret Sub-band level) of the secret image(compressed image) Through a secret algorithm and then was minimized transaction values of sub bands level of image want to hide, the key used (random generated Key)to hide the secret, and this system has the property of the secret high in the process of concealment and the distribution of transactions analyzed for the image want to hide After the hit was so secret key and collected(adding) with the sub band level of the cover image on the adoption of the proposal are known algorithm with the secret key for both the sender and the receiver.

In this paper, we studied the effects of voice codecs on remote speaker recognition system, considering three types of speech codec: PCM, DPCM and ADPCM conforming to International Telecommunications Union Telecoms (ITU-T) recommendation used in telephony and VoIP (Voice over Internet Protocol). To improve the performance of speaker recognition in a noisy environment, we propose a new speech activity detection algorithm (SAD) using ''Adaptive Threshold'', which can be simulated with speech wave files of TIMIT (Texas Instruments Massachusetts Institute of Technology) database that allows recognition system to be done under almost ideal conditions. Moreover, the speaker recognition system is based on Vector Quantization as speaker modeling technique and Mel Frequency Cepstral Coefficient (MFCC) as feature extraction technique. Where, the feature extraction proceed after (for testing phase) and before (for training phase) the speech is sending over communication channel...

In this work, we present results on the effect of well-known mixed excitation linear prediction (MELP) and code-excited linear prediction (CELP) codecs (coder/decoder) on voicing and vocal tract parameters of Arabic sounds. The study shows that the spectral distortion is large compared to other studies and is largest for MELP1200. Vowel formants have a shift which may exceed one critical band below or above its reference value. Finally, it was found that the coded pitch period did not suffer any significant change through the coding/decoding process.

Voice over Internet Protocol (VoIP) is a popular and important internet protocol for real-time voice calling. It is used in several software applications such as Skype, WhatsApp, and Google Talk. However, communications over the internet can easily be exposed to hacking and eavesdropping. In secret communication, a private channel with robust encryption can provide the required protection for the communications. But private channels have more constraints than the public channel, such as specific communication devices and specific regions to cover. On the other hand, public communications such as VoIP can be done from anywhere without extra costs. This paper proposes a real-time covert communication approach that generates a secret speech channel inside a public speech channel based on audio steganography. The process requires high embedding capacity in a real-time manner. Therefore, the proposed approach encodes the secret speech using Internet Low Bit Rate Codec (iLBC) that can be used as a VoIP source Codec to compress the secret input speech with auto-correction for speech quality degradation over a lossy channel. Also, the cover speech is compressed by G.711 encoder at synchronous time periods (for each 20 ms) with respect to the secret speech to meet the requirements of the VoIP. Subsequently, the secret data hides in compressed cover speech data in real-time. The embedding procedure employs the only high strength data to maintain the quality of the cover data after embedding at greater than 40 dB in terms of signal-to-noise ratio (S NR). The secret data is 100% retrieved without error in the case of a lossless channel. This approach can be used in secure communications such as military and government communications.

The growth of the cellular technology and wireless networks all over the world has increased the demand for digital information by manifold. This massive demand poses difficulties for handling huge amounts of data that need to be stored and transferred. To overcome this problem we can compress the information by removing the redundancies present in it. Redundancies are the major source of generating errors and noisy signals. Coding in MATLAB helps in analyzing compression of speech signals with varying bit rate and remove errors and noisy signals from the speech signals. Speech signal's bit rate can also be reduced to remove error and noisy signals which is suitable for remote broadcast lines, studio links, satellite transmission of high quality audio and voice over internet This paper focuses on speech compression process and its analysis through MATLAB by which processed speech signal can be heard with clarity and in noiseless mode at the receiver end .

Voice over Internet Prototcol (VoIP) is a technology to carry voice calls over the internet. It is a technology to replace the traditional Public Switched telephone Network (PSTN). VoIP is a growing technology. Its functions, facilities and features must overcome the PSTN. There are a lot of inconveniences faced by VoIP users. They are packet loss, dealy, security, throughput, echo and Quality of Service (QoS). The security and packet loss are severe and serious problem which affects the quality of service in real time interactive applications. During transmission the packets may loss or it may lead to theft. This paper addresses the security mechanisms of VoIP using modified secret sharing algorithm in a multipath environment. The simulation results show that the quality of service and the security is improved in a better way.

Large-scale numerical simulations of high-intensity focused ultrasound (HIFU), important for model-based treatment planning, generate large amounts of data. Typically, it is necessary to save hundreds of gigabytes during simulation. We propose a novel algorithm for time-varying simulation data compression specialised for HIFU. Our approach is particularly focused on on-the-fly parallel data compression during simulations. The algorithm is able to compress 3D pressure time series of linear and non-linear simulations with very acceptable compression ratios and errors (over 80% of the space can be saved with an acceptable error). The proposed compression enables significant reduction of resources, such as storage space, network bandwidth, CPU time, and so forth, enabling better treatment planning using fast volume data visualisations. The paper describes the proposed method, its experimental evaluation, and comparisons to the state of the arts.

This paper gives an idea about the importance of speech enhancement and the performance analysis of DWT and Kalman filter based speech enhancement techniques. The objectives of Speech Enhancement vary widely reduction of noise level, increased intelligibility, reduction of auditory fatigue, etc. Speech processing systems are depending on the nature of the noise, and often on the signal-to-noise ratio (SNR) of the distorted speech. Enhancement of degraded speech is useful in aircraft, mobile, military and commercial communication. Basically speech enhancement methods are available in time domain and transform domain approach. In this paper we are going to discuss about Kalman filter and Wavelet Transform based enhancement techniques which gives good results in high noise environment when compared to other techniques. The performance of these methods can be evaluated using PSNR and Mean Square Error (MSE).

Speech compression is a mature technology with many applications. Over the past decade, huge advances have been made in the area of speech coding for reduced bit-rate transmission. With perceptual audio coding, the signal is coded efficiently using a psychoacoustic model, as in MPEG standards. In this paper, two well known algorithms, LPC (Linear Predictive Coding) and subband coding are combined to reduce data transmission rate from 128 Kbps to as low as 12 Kbps at minimum complexity and implemented on a digital signal processor. The performance of the proposed algorithm is almost same as the MPEG algorithm without its complexity.

Speech coding deals with the problem of reducing the bit rate required for representing speech signals while preserving the quality of the speech reconstructed from that representation. In this paper, we propose a novel speech coding technique, not only to compress speech signal at low bit rate, but also to maintain its quality even if the received signal is corrupted by noise. The encoder of the proposed technique is based on speech analysis/synthesis model using a sinusoidal representation where the sinusoidal components are involved to form a nearly resemblance of the original speech waveform. In the proposed technique, the original frame is divided to voiced or unvoiced sub-frames based on their energies. The aim of the division and classification is to choose the best parameters that reduce the total bit rate and enable the receiver to recover the speech signal with a good quality. The parameters involved in the analysis stage are extracted from the short-time Fourier transform where the original speech signal is converted into frequency domain. Making use of the peak-picking technique, amplitudes of the selected peaks with their associated frequencies and phases of the original speech signal are extracted. In the next stage, novel parameter reduction and quantization techniques are performed to reduce the bit rate while preserving the quality of the recovered signal.

Cryptography, the scheme of information stashing and verification, entirely deals with protocols, algorithms and strategies to ensure the precise security facility of the signal consistently by hindering unauthorized access to the confidential information. Albeit in most of the encryption schemes, certain impediments are faced by the service providers such as the expansion of required bandwidth, the fragile encryption technique, the consumption of maximum bandwidth in security purpose, less priority to improvement of SNR of the system, the complexity in decryption and so forth. This paper illustrates the SNR enhancement & bandwidth optimization technique in security purpose using PCM-DSSS sample by sample encryption scheme. For this purpose, after sampling of a signal, simple mathematical operation is performed in each sample with a time varying arbitrary weights. This arbitrary weight can be obtained from D/A conversion of pseudo noise sequence. Since the bandwidth consumption in security purpose can be minimized in this scheme, a significant portion of unused bandwidth can be used to improve the SNR of the system by reducing quantization noise of encrypted samples. By the same token, the possibility of SNR improvement is demonstrated by reckoning the quantization noise while introducing additional quantization step.

The purpose of this study is to describe text-to-speech system for the Tigrigna language, using dialog fusion architecture and developing a prototype text-to-speech synthesizer for Tigrigna Language. Methods : The direct observation and review of articles are applied in this research paper to identify the whole strings which are represented the language. Tools used in this work are Mathlab, LPC, and python. In this paper LSTM deep learning model was applied to find out accuracy, precision, recall, and Fscore. Findings: The overall performance of the system in the word level which is evaluated by NeoSpeech tool is found to be 78% which is fruitful. When it comes to the intelligibility and naturalness of the synthesized speech in the sentence level, it is measured in MOS scale and the overall intelligibility and naturalness of the system are found to be 3.28 and 3.27 respectively. Based on the experiment LSTM Deep learning model provides an accuracy of 91.05%, the precision of 78.05%, recall of 86.59 %, and F-score of 83.05% respectively. The values of performance, intelligibility, and naturalness are inspiring and show that diphone speech units are good candidates to develop a fully functional speech synthesizer. Novelty: The researchers come up with the first text to speech LSTM deep learning model for the Tigrigna language which is critical and will be a baseline for other related research to be done for Tigrigna and other languages.

In this paper, we studied the effects of voice codecs on remote speaker recognition system, considering three types of speech codec: PCM, DPCM and ADPCM conforming to International Telecommunications Union Telecoms (ITU-T) recommendation used in telephony and VoIP (Voice over Internet Protocol). To improve the performance of speaker recognition in a noisy environment, we propose a new speech activity detection algorithm (SAD) using ''Adaptive Threshold'', which can be simulated with speech wave files of TIMIT (Texas Instruments Massachusetts Institute of Technology) database that allows recognition system to be done under almost ideal conditions. Moreover, the speaker recognition system is based on Vector Quantization as speaker modeling technique and Mel Frequency Cepstral Coefficient (MFCC) as feature extraction technique. Where, the feature extraction proceed after (for testing phase) and before (for training phase) the speech is sending over communication channel...

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Speech generation is one of the most important areas of research in speech signal processing which is now gaining a serious attention. Speech is a natural form of communication in all living things. Computers with the ability to understand speech and speak with a human like voice are expected to contribute to the development of more natural man-machine interface. However, in order to give those functions that are even closer to those of human beings, we must learn more about the mechanisms by which speech is produced and perceived, and develop speech information processing technologies that can generate a more natural sounding systems. The so described field of stud, also called speech synthesis and more prominently acknowledged as text-to-speech synthesis, originated in the mid eighties because of the emergence of DSP and the rapid advancement of VLSI techniques. To understand this field of speech, it is necessary to understand the basic theory of speech production. Every language ...

Speech is an important biological signal for primary mode of communication among human being and also the most natural and efficient form of exchanging information among human in speech. Speech processing is the most important aspect in signal processing. In this paper the theory of linear algebra called singular value decomposition (SVD) is applied to the speech signal. SVD is a technique for deriving important parameters of a signal. The parameters derived using SVD may further be reduced by perceptual evaluation of the synthesized speech using only perceptually important parameters, where the speech signal can be compressed so that the information can be transformed into compressed form without losing its quality. This technique finds wide applications in speech compression, speech recognition, and speech synthesis. The objective of this paper is to investigate the effect of SVD based feature selection of the input speech on the perception of the processed speech signal. The speech signal which is in the form of vowels \a\, \e\, \u\ were recorded from each of the six speakers (3 males and 3 females). The vowels for the six speakers were analyzed using SVD based processing and the effect of the reduction in singular values was investigated on the perception of the resynthesized vowels using reduced singular values. Investigations have shown that the number of singular values can be drastically reduced without significantly affecting the perception of the vowels.

As the technology is rapidly advancing day by day sharing of information over the internet is experiencing an explosive growth, which in turn is also posing new threats and vulnerabilities in the existing systems. The quest for more stronger and reliable methodologies to tackle the security issues is unending. In this direction a new cryptographic method is proposed in this paper based on Layered Cellular Automata (LRCA) and the strengths are analyzed in comparison with the existing systems. Index Terms – Cellular Automata (CA), Reversible Cellular Automata (RCA), Layered Cellular Automata, Symmetric key, Encryption. I.INTRODUCTION Over the past two decades Cryptographic techniques have become essential part of any secure digital communication. All the cryptosystems can be classified in two types Private key systems and Public key systems. In symmetric key system both the sender and receiver use the same key to reveal the information (also called as secret key encryption). In public...

In this paper, we studied the effects of voice codecs on remote speaker recognition system, considering three types of speech codec: PCM, DPCM and ADPCM conforming to International Telecommunications Union-Telecoms (ITU-T) recommendation used in telephony and VoIP (Voice over Internet Protocol). To improve the performance of speaker recognition in a noisy environment, we propose a new speech activity detection algorithm (SAD) using ''Adaptive Threshold'', which can be simulated with speech wave files of TIMIT (Texas Instruments Massachusetts Institute of Technology) database that allows recognition system to be done under almost ideal conditions. Moreover, the speaker recognition system is based on Vector Quantization as speaker modeling technique and Mel Frequency Cepstral Coefficient (MFCC) as feature extraction technique. Where, the feature extraction proceed after (for testing phase) and before (for training phase) the speech is sending over communication channel. Therefore, the digital channels can introduce several types of degradation. To overcome the channel degradation, a convolutional code is used as error-control coding with AWGN channel. Finely, In our simulation with Matlab we have used 30 speakers of different regions (10 male and 20female), the best overall performance of speech codecs was observed for the PCM code in terms of recognition rate accuracy and runtime.

The tremendous growth of digital data has led to a high necessity for compressing applications either to minimize memory usage or transmission speed. Despite of the fact that many techniques already exist, there is still space and need for new techniques in this area of study. With this paper we aim to introduce a new technique for data compression through pixel combinations, used for both lossless and lossy compression. This new technique is also able to be used as a standalone solution, or with some other data compression method as an add-on providing better results. It is here applied only on images but it can be easily modified to work on any other type of data. We are going to present a side-by-side comparison, in terms of compression rate, of our technique with other widely used image compression methods. We will show that the compression ratio achieved by this technique tanks among the best in the literature whilst the actual algorithm remains simple and easily extensible. Fi...

The tremendous growth of digital data has led to a high necessity for compressing applications either to minimize memory usage or transmission speed. Despite of the fact that many techniques already exist, there is still space and need for new techniques in this area of study. With this paper we aim to introduce a new technique for data compression through pixel combinations, used for both lossless and lossy compression. This new technique is also able to be used as a standalone solution, or with some other data compression method as an add-on providing better results. It is here applied only on images but it can be easily modified to work on any other type of data. We are going to present a side-by-side comparison, in terms of compression rate, of our technique with other widely used image compression methods. We will show that the compression ratio achieved by this technique tanks among the best in the literature whilst the actual algorithm remains simple and easily extensible. Fi...