For the past several decades, designers have processed speech for a wide variety of applications ... more For the past several decades, designers have processed speech for a wide variety of applications ranging from mobile communications to automatic reading machines. Speech recognition reduces the overhead caused by alternate communication methods. Speech has not been used much in the field of electronics and computers due to the complexity and variety of speech signals and sounds. However, with modern processes, algorithms, and methods we can process speech signals easily and recognize the text. In this project, we are going to develop an on-line speech-to-text engine. The system acquires speech at run time through a microphone and processes the sampled speech to recognize the uttered text. The recognized text can be stored in a file. We are developing this on android platform using eclipse workbench. Our speech-to-text system directly acquires and converts speech to text. It can supplement other larger systems, giving users a different choice for data entry. A speech-to-text system c...
Ample Data Exploration and Map Reduce Indoctrination Decisive Factor
International Journal of Research, 2018
This immense volume of information of knowledge of information is thought as huge data. The info ... more This immense volume of information of knowledge of information is thought as huge data. The info flow therefore quick that the overall accumulation of the past 2 years is currently a zettabyte. Huge information refers to technologies and initiatives that involve information that's too various, fast-changing or huge for typical technologies, skills and infrastructure to deal with efficiency. Information currently stream from way of life from phones and credit cards and televisions and computers; from the infrastructure of cities from sensor-equipped buildings, trains, buses, planes, bridges, and factories. Aforesaid otherwise, the volume, rate or kind of information is just too nice. The amount {of information of knowledge of information with the speed it's generated makes it tough for this computing infrastructure to handle huge data. to beat this downside, huge processing are often performed through a programming paradigm called MapReduce. Typical, implementation of the MapReduce paradigm needs networked connected storage and multiprocessing. Hadoop and HDFS by apache are wide used for storing and managing huge information. During this analysis paper the authors recommend numerous ways for line of work to the issues in hand through MapReduce framework over HDFS. MapReduce technique has been studied at during this paper that is required for implementing huge information analysis victimization HDFS. In this paper, we have a tendency to gift a outline of our activities related to the storage and query process of Google 1T 5-gram information set. Tendency to 1st provides a transient introduction to a number of the implementation techniques for the relative pure mathematics followed by a Map scale back implementation of equivalent operators. We have a tendency to then implement a info schema in Hive for the Google 1T 5-gram data set. This paper can more look at the question process with Hive and Pig within the Hadoop setting. More specifically, we have a tendency to report statistics for our queries during this setting.
Peer to Peer Networks - A Review & Study on Load Balancing
Peer-to-peer (P2P) systems increase the popularity and have become a dominant means for sharing r... more Peer-to-peer (P2P) systems increase the popularity and have become a dominant means for sharing resources. In these systems, load balancing is one of challenge issue because nodes are often heterogeneous. While several load-balancing schemes, these solutions are typically ad hoc, heuristic based, and localized. In the analysis a general framework, HiGLOB, for global load balancing in structured P2P systems, each node in HiGLOB has a histogram manager maintains a histogram that reflects a global view of the distribution of the load in the system, and a load- balancing manager that redistributes the load whenever the node becomes overloaded or then exploit the routing metadata to partition the P2P network into no overlapping regions corresponding to the histogram buckets, mechanisms to keep the cost of constructing and maintaining the histograms low. Comparison analysis shows that our scheme can control and bound the amount of load imbalance across the system.
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Papers by E Mahender