Tamil Phonemes Recognition for Normal and Hearing Impaired: A Survey Janakiraman.S Pondicherry University, Puducherry, INDIA Pavithra.S Research Scholar, Sathiyabama University Chennai, Tamil Nadu, INDIA __________________________________________________________________________________________ Abstract: This paper presents a survey on speech recognition models and Tamil Phonemes Recognition Mod...

This contribution presents potential straightforward technique to extract temporal information in auditory domain. Even though the final phoneme accuracy is comparable to the traditional approach, it can be well suited to replace standard spectrum based techniques used in ASR systems due to higher flexibility and computational inexpensiveness.

This paper introduces a novel approach for generating multilingual text-to-phoneme mappings for use in multilingual speech recognition systems. The multilingual mappings are based on the weighted outputs from a neural network text-to-phoneme model, trained on data mixed from several languages. The multilingual mappings used together with a branched grammar decoding scheme is able to capture bot...

Automatic speech recognition systems apply grapheme-to phoneme transcription (G2P) to model pronunciation of items in the lexicon. General purpose G2P transcriptions are not always accurate, e.g., in a multilingual environment. To improve the transcription quality, G2P transcriptions can be postprocessed using a phoneme-to-phoneme (P2P) converter. This paper discusses the applicability of P2P t...

In this paper, we propose a statistical method of evaluating the pronunciation proficiency for presentation in English. We statistically analyze the utterances to find a combination that has a high correlation between an English teacher’s score and some acoustic features. We found that ratio of the likelihoods of free phoneme recognition by using native English HMMs and nonnative English HMMs w...

The study of a system for Vietnamese continuous digit recognition is described. The CSLU Toolkit was used to develop and implement hybrid HMM/ANN recognition systems. Experiments were done with a corpus of 442 sentences with 2340 words, which were extracted from two telephone-speech corpora: \22 Language v1.2" and \MultiLanguage Telephone Speech v1.2". In our experiments, a context-dependent ph...

In this paper, we propose speaker-dependent multiple-pronunciation lexical modeling for improving the performance of dysarthric automatic speech recognition (ASR). For each dysarthric speaker, a phoneme confusion matrix is first constructed from the results of phoneme recognition. Then, pronunciation variation rules are extracted by investigating the phoneme confusion matrix, and they are incor...

In this work, the application of across-word phoneme models during large vocabulary continuous speech recognition is studied. A recognition system will be developed which allows for the training of high performance across-word phoneme models, the efficient application of these across-word phoneme models in combination with long-span language models in one single search pass, and the constructio...

This paper proposes imitated phoneme models that represent non-verbal sounds, especially cough sounds here, as phoneme sequences. The purpose of this research is to detect the cough sounds from user utterances accurately for the home health care task because coughing is one of the most important barometers to check the health condition. To deal with the variety of the cough sounds, the imitated...