• Corpus ID: 14478681

Speech Recognition : Statistical Methods 1 Speech Recognition : Statistical M ethods

  title={Speech Recognition : Statistical Methods 1 Speech Recognition : Statistical M ethods},
  author={Lawrence R. Rabiner},
The goal of getting a machine to understand fluently spoken speech and respond in a natural voice has been driving speech research for more than 50 years. Although the personification of an intelligent machine such as HAL in the movie 2001, A Space Odyssey, or R2D2 in the Star Wars series, has been around for more than 35 years, we are still not yet at the point where machines reliably understand fluent speech, spoken by anyone, and in any acoustic environment. In spite of the remaining… 
2 Citations

Speech recognition using Hilbert-Huang transform based features

HFCCs use the Hilbert-Huang Transform (HHT) instead of the windowing and the FT scheme used in MFCCs, which enables it to obtain a high frequency resolution representation of the signal regardless of the duration of the time window used.

Smart device controlling through voice commands given in malayalam language

In this paper, a new method to read and recognize the voice command given in Malayalam language with the help of advanced language processing algorithms. Tensor flow is taken as the tool for voice



Automatic recognition and understanding of spoken language - a first step toward natural human-machine communication

An accurate overview of spoken language technology is presented as a basis to inspire future advances and the limitations of the current technology are discussed, and the challenges that are ahead are pointed out.

An Overview of Automatic Speech Recognition

This chapter reviews some of the key advances in several areas of automatic speech recognition and addresses technical challenges that need to be faced in order to reach the ultimate goal of providing an easy-to-use, natural, and flexible voice interface between people and machines.

Survey of the state of the art in human language technology

A speech interface, in a user's own language, is ideal because it is the most natural, exible, eecient, and economical form of human communication.

SWITCHBOARD: telephone speech corpus for research and development

  • J. GodfreyE. HollimanJ. McDaniel
  • Physics, Linguistics
    [Proceedings] ICASSP-92: 1992 IEEE International Conference on Acoustics, Speech, and Signal Processing
  • 1992
SWITCHBOARD is a large multispeaker corpus of conversational speech and text which should be of interest to researchers in speaker authentication and large vocabulary speech recognition. About 2500

Stochastic pronunciation modelling from hand-labelled phonetic corpora

Cepstral analysis technique for automatic speaker verification

New techniques for automatic speaker verification using telephone speech based on a set of functions of time obtained from acoustic analysis of a fixed, sentence-long utterance using a new time warping method using a dynamic programming technique.

Evaluation of the CMU ATIS System

The CMU Phoenix system is an experiment in understanding spontaneous speech that uses a bigram language model with the Sphinx speech recognition system and applies grammatical constraints at the phrase level and to use semantic rather than lexical grammars.

Benchmark Tests for the DARPA Spoken Language Program

These tests were reported on and discussed in detail at the Spoken Language Systems Technology Workshop held at the Massachusetts Institute of Technology, January 20-22, 1993.