Introduction to the Special Section on Voice Transformation

2013

Generally defined, speech modification is the process of changing certain perceptual properties of speech while leaving other properties unchanged. Among the many types of speech information that may be altered are rate of articulation, pitch and formant characteristics.Modifying the speech parameters like pitch, duration and strength of excitation by desired factor is termed as prosody modification. In this thesis prosody modifications for voice conversion framework are presented. Among all the speech modifications for prosody two things are important firstly modification of duartion and pauses (Time scale modification) in a speech utterance and secondly modification of the pitch(pitch scale modification).Prosody modification involves changing the pitch and duration of speech without affecting the message and naturalness.In this work time scale and pitch scale modifications of speech are discussed using two methods Time Domain Pitch Synchronous Overlapped-Add (TD-PSOLA) and epoch b...

International Journal of Speech Technology, 2005

This paper presents a method for the estimation and mapping of parametric models of speech resonance at formants for voice conversion. The spectral features at formants that contribute to voice characteristics are the trajectories of the frequencies, the bandwidths and intensities of the resonance at formants. The formant features are extracted from the poles of a linear prediction (LP) model of speech. The statistical distributions of formants are modelled by a two-dimensional hidden Markov model (HMM) spanning the time and frequency dimensions. Experimental results are presented which show a close match between HMM-based formant models and the histograms of formants. For voice conversion two alternative methods are explored for mapping the formants of a source speaker to those of a target speaker. The first method is based on an adaptive formant-tracking warping of the frequency response of the LP model and the second method is based on the rotation of the poles of the LP model of speech. Both methods transform all spectral parameters of the resonance at formants of the source speaker towards those of the target speaker. In addition, the issues affecting the selection of the warping ratios for the mapping functions are investigated. Experimental results of formant estimation and perceptual evaluation of voice morphing based on parametric formant models are presented.

IEEE Transactions on Audio, Speech, and Language Processing, 2000

In Voice Conversion (VC), the speech of a source speaker is modified to resemble that of a particular target speaker. Currently, standard VC approaches use Gaussian mixture model (GMM)-based transformations that do not generate high-quality converted speech due to "over-smoothing" resulting from weak links between individual source and target frame parameters. Dynamic Frequency Warping (DFW) offers an appealing alternative to GMM-based methods, as more spectral details are maintained in transformation; however, the speaker timbre is less successfully converted because spectral power is not adjusted explicitly. Previous work combines separate GMM-and DFW-transformed spectral envelopes for each frame. This paper proposes a more effective DFW-based approach that 1) does not rely on the baseline GMM methods, and 2) functions on the acoustic class level. To adjust spectral power, an amplitude scaling function is used that compares the average target and warped source log spectra for each acoustic class. The proposed DFW with Amplitude scaling (DFWA) outperforms standard GMM and hybrid GMM-DFW methods for VC in terms of both speech quality and timbre conversion, as is confirmed in extensive objective and subjective testing. Furthermore, by not requiring time-alignment of source and target speech, DFWA is able to perform equally well using parallel or nonparallel corpora, as is demonstrated explicitly.

IRCAM has a long experience in analysis, synthesis and transformation of voice. Natural voice transformations are of great interest for many applications and can be combine with text-to-speech system, leading to a powerful creation tool. We present research conducted at IRCAM on voice transformations for the last few years. Transformations can be achieved in a global way by modifying pitch, spectral envelope, durations etc. While it sacrifices the possibility to attain a specific target voice, the approach allows the production of new voices of a high degree of naturalness with different gender and age, modified vocal quality, or another speech style. These transformations can be applied in realtime using ircamTools TRAX.Transformation can also be done in a more specific way in order to transform a voice towards the voice of a target speaker. Finally, we present some recent research on the transformation of expressivity.

Speech Communication, 2006

This paper presents a voice transformation algorithm which modifies the speech of a source speaker such that it is perceived as if spoken by a target speaker. A novel method which is based on dynamic programming approach is proposed. The designed system obtains speaker-specific codebooks of line spectral frequencies (LSFs) for both source and target speakers. Those codebooks are used to train a mapping histogram matrix, which is used for LSF transformation from one speaker to the other. The baseline system uses the maxima of the histogram matrix for LSF transformation. The shortcomings of this system, which are the limitations of the target LSF space and the spectral discontinuities due to independent mapping of subsequent frames, have been overcome by applying the dynamic programming approach. Dynamic programming approach tries to model the long-term behaviour of LSFs of the target speaker, while it is trying to preserve the relationship between the subsequent frames of the source LSFs, during transformation. Both objective and subjective evaluations have been conducted and it has been shown that dynamic programming approach improves the performance of the system in terms of both the speech quality and speaker similarity.

Abstract IRCAM has a long experience in analysis, synthesis and transformation of voice. Natural voice transformations are of great interest for many applications and can be combine with text-to-speech system, leading to a powerful creation tool. We present research conducted at IRCAM on voice transformations for the last few years. Transformations can be achieved in a global way by modifying pitch, spectral envelope, durations etc.

Signals, 2021

Voice transformation, for example, from a male speaker to a female speaker, is achieved here using a two-level dynamic warping algorithm in conjunction with an artificial neural network. An outer warping process which temporally aligns blocks of speech (dynamic time warp, DTW) invokes an inner warping process, which spectrally aligns based on magnitude spectra (dynamic frequency warp, DFW). The mapping function produced by inner dynamic frequency warp is used to move spectral information from a source speaker to a target speaker. Artifacts arising from this amplitude spectral mapping are reduced by reconstructing phase information. Information obtained by this process is used to train an artificial neural network to produce spectral warping information based on spectral input data. The performance of the speech mapping compared using Mel-Cepstral Distortion (MCD) with previous voice transformation research, and it is shown to perform better than other methods, based on their reporte...

2011 International Conference on Uncertainty Reasoning and Knowledge Engineering, 2011

Recently, a lot of works has been done in speech technology. Text-to-Speech and Automatic Speech Recognition have been the priorities in research efforts to improve the human-machine interaction. The ways to improve naturalness in human-machine interaction is becoming an inportant matter of concern. Voice conversion can be served as a useful tools to provide new insights related to personification of speech enabled systems. In this research, there are two main parameters are considered vocal tract structure and pitch. For conversion process speech is resolved in two components, excitation component and filtered component using Linear Predictive Coding (LPC). Ptich is determined by autocorrelation. After obtained the acoustic components from source speaker and target speaker, then the acoustic components will be mapped one-to-one to replaced the the acoustic feature from source speaker to target speaker. At least, signal is modified by resynthesis so the resulted speech would perceive as if spoken by target speaker.

Proc. of the ICSLP'04, 2004

Voice Conversion (VC) systems modify a speaker voice (source speaker) to be perceived as if another speaker (target speaker) had uttered it. Previous published VC approaches using Gaussian Mixture Models [1] performs the conversion in a frame-by-frame basis using only spectral information. In this paper, two new approaches are studied in order to extend the GMM-based VC systems. First, dynamic information is used to build the speaker acoustic model. So, the transformation is carried out according to sequences of frames. Then, phonetic information is introduced in the training of the VC system. Objective and perceptual results compare the performance of the proposed systems.

Proc. Speech …, 2010

This paper proposes an approach to transform speech from a neutral style into other expressive styles using both prosody and voice quality (VoQ). The main aim is to validate the usefulness of VoQ in the enhancement of expressive synthetic speech. A Harmonic plus Noise Model (HNM) is used to modify speech following a set of rules extracted from an expressive speech corpus with five categories (neutral, happy, sensual, aggressive and sad). Finally, modified speech utterances were used to perform a perceptual test. These results indicate that listeners prefer prosody together with VoQ transformation instead of only prosody modification.