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Volumn 12, Issue 1, 2009, Pages 47-57

Syllable modeling in continuous speech recognition for Tamil language

Author keywords

Context dependent; Context independent; Continuous speech recognition; Hidden Markov model; Syllable; Tamil language; Triphone

Indexed keywords

ACOUSTIC MODEL; AUTOMATIC SPEECH RECOGNITION; CONTEXT DEPENDENT; CONTEXT INDEPENDENT; GAINING MOMENTUM; MONOPHONES; OUT OF VOCABULARY WORDS; TAMIL LANGUAGE; TRIPHONES; WORD ERROR RATE; WORD MODELS;

EID: 72149134486     PISSN: 13812416     EISSN: 15728110     Source Type: Journal    
DOI: 10.1007/s10772-009-9058-0     Document Type: Article
Times cited : (23)

References (27)
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  • 12
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  • 14
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    • A syllable based continuous speech recognizer for Tamil
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    • Lakshmi, A.1    Hema, A.M.2
  • 16
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    • Context-dependent phonetic hidden Markov models for speaker-independent continuous speech recognition
    • DOI 10.1109/29.52701
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    • Nagarajan, T.1    Hema, A.M.2    Hegde, R.M.3
  • 25
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    • Comparison of performance of enhanced morpheme-based language model with different word-based language models for improving the performance of Tamil speech recognition system
    • Article 9
    • Saraswathi, S., & Geetha, T. V. (2007). Comparison of performance of enhanced morpheme-based language model with different word-based language models for improving the performance of Tamil speech recognition system. ACM Transaction on Asian Language Information Processing, 6(3), Article 9.
    • (2007) ACM Transaction on Asian Language Information Processing , vol.6 , Issue.3
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    • Accent in Tamil: Speech research for speech technology
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    • Soundaraj, F. (2000). Accent in Tamil: Speech research for speech technology. In K. Nagamma Reddy (Ed.), Speech technology: Issues and implications in Indian languages (pp. 246-256). Thiruvananthapuram: International School of Dravidian Linguistics.
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    • Soundaraj, F.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.