Fast Automatic Speech Recognition Training

نویسندگان

  • Jerzy Sas
  • Bogumila Hnatkowska
چکیده

The novel approach to speaker adaptation within speech recognition system basing on late clustering of prototype speakers is presented. For a new speaker the speaker prototype is created dynamically on the basis of selected remembered prototypes that are similar enough to the new one. The training utterances are prepared in an optimized way to decrease training duration without negative influence on recognition accuracy. Keywords—speech recognition system, speaker adaptation, supervised adaptation, acoustic models, clustering

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

A Database for Automatic Persian Speech Emotion Recognition: Collection, Processing and Evaluation

Abstract   Recent developments in robotics automation have motivated researchers to improve the efficiency of interactive systems by making a natural man-machine interaction. Since speech is the most popular method of communication, recognizing human emotions from speech signal becomes a challenging research topic known as Speech Emotion Recognition (SER). In this study, we propose a Persian em...

متن کامل

ACOUSTIC MODEL ADAPTATION FOR AUTOMATIC SPEECH RECOGNITION AND ANIMAL VOCALIZATION CLASSIFICATION by

ACOUSTIC MODEL ADAPTATION FOR AUTOMATIC SPEECH RECOGNITION AND ANIMAL VOCALIZATION CLASSIFICATION Jidong Tao, B.Eng., M.S. Marquette University, 2009 Automatic speech recognition (ASR) converts human speech to readable text. Acoustic model adaptation, also called speaker adaptation, is one of the most promising techniques in ASR for improving recognition accuracy. Adaptation works by tuning a g...

متن کامل

A TMS320C40 based Speech Recognition System for Embedded Applications

This paper describes a prototype implementation of a speech recognition system for embedded applications. The recognition system is comprised of a feature extractor and a classifier. The feature extractor is based on a 64-point Fast Fourier Transformation (FFT); the classifier is based on discrete-density Hidden Markov Models (HMM) with a variable codebook size. Training as well as classificati...

متن کامل

Designing and implementing a system for Automatic recognition of Persian letters by Lip-reading using image processing methods

For many years, speech has been the most natural and efficient means of information exchange for human beings. With the advancement of technology and the prevalence of computer usage, the design and production of speech recognition systems have been considered by researchers. Among this, lip-reading techniques encountered with many challenges for speech recognition, that one of the challenges b...

متن کامل

Utterance Selection for Optimizing Intelligibility of TTS Voices Trained on ASR Data

This paper describes experiments in training HMM-based text-to-speech (TTS) voices on data collected for Automatic Speech Recognition (ASR) training. We compare a number of filtering techniques designed to identify the best utterances from a noisy, multi-speaker corpus for training voices, to exclude speech containing noise and to include speech close in nature to more traditionally-collected T...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 2009