Using genetic algorithms for rapid speaker adaptation
نویسندگان
چکیده
This paper proposes two new approaches to rapid speaker adaptation of acoustic models by using genetic algorithms. Whereas conventional speaker adaptation techniques yield adapted models which represent local optimum solutions, genetic algorithms are capable to provide multiple optimal solutions, thereby delivering potentially more robust adapted models. We have investigated two different strategies of application of the genetic algorithm in the framework of speaker adaptation of acoustic models. The first approach ( ) consists in using a genetic algorithm to adapt the set of Gaussian means to a new speaker. The second approach ( ) uses the genetic algorithm to enrich the set of speaker-dependant systems employed by the EigenVoices. Experiments with the Resource Management corpus show that, with one adaptation utterance, GA can improve the performances of a speaker-independant system as efficiently as EigenVoices. The method outperforms EigenVoices.
منابع مشابه
Speaker Adaptation in Continuous Speech Recognition Using MLLR-Based MAP Estimation
A variety of methods are used for speaker adaptation in speech recognition. In some techniques, such as MAP estimation, only the models with available training data are updated. Hence, large amounts of training data are required in order to have significant recognition improvements. In some others, such as MLLR, where several general transformations are applied to model clusters, the results ar...
متن کاملSpeaker Adaptation in Continuous Speech Recognition Using MLLR-Based MAP Estimation
A variety of methods are used for speaker adaptation in speech recognition. In some techniques, such as MAP estimation, only the models with available training data are updated. Hence, large amounts of training data are required in order to have significant recognition improvements. In some others, such as MLLR, where several general transformations are applied to model clusters, the results ar...
متن کاملImproving EigenVoices-based techniques and SMLLR for Speaker Adaptation by combining EV and SMLLR techniques or using Genetic Algorithms
This paper constitutes a study of several classical and original methods for a speaker adaptation of the acoustic hidden Markov models of an automatic speech recognition system (ASRS). Most of today’s real applications require that the speaker adaptation process continuously improves the performance of the underlying ASRS, as more utterances are pronounced by a new speaker. The first part of th...
متن کاملEigenspace-based speaker adaptation methods in Persian speech recognition systems
Among speaker adaptation algorithms, eigenvoice (EV) and eigenspace-based MLLR (EMLLR) adaptation approaches have been proposed for rapid adaptation with very limited adaptation data. In these methods, a speaker adapted model is constrained to be a weighted combination of some orthogonal basis vectors. In this manner, both the number of parameters to be estimated from the adaptation data, and t...
متن کاملDoctoral Dissertation Rapid Unsupervised Speaker Adaptation Based on Sufficient Statistics of Hidden Markov Models
In realizing a speech recognition system robust to variation of speakers, an efficient adaptation algorithm is needed. Most adaptation techniques require many adaptation data to carry out an adaptation task. Adaptation data are often collected from the actual speaker itself in several utterances. With the time needed to gather and transcribe the adaptation utterances, together with the actual e...
متن کامل