抄録
We present a method that determines articulatory movements from speech acoustics using an HMM (Hidden Markov Model)-based speech production model. The model statistically generates speech acoustics and articulatory movements from a given phonemic string. It consists of HMMs of articulatory movements for each phoneme and an articulatory-to-acoustic mapping for each HMM state. For a given speech acoustics, the maximum a posteriori probability estimate of the articulatory parameters of the statistical model is presented. The method's performance on sentences was evaluated by comparing the estimated articulatory parameters with observed parameters. The average rms error of the estimated articulatory parameters was 1.79 mm with phonemic information and 2.16 mm without phonemic information in an utterance.
| 元の言語 | English |
|---|---|
| ホスト出版物のタイトル | 7th International Conference on Spoken Language Processing, ICSLP 2002 |
| 出版者 | International Speech Communication Association |
| ページ | 2305-2308 |
| ページ数 | 4 |
| 出版物ステータス | Published - 2002 |
| 外部発表 | Yes |
| イベント | 7th International Conference on Spoken Language Processing, ICSLP 2002 - Denver, United States 継続期間: 2002 9 16 → 2002 9 20 |
Other
| Other | 7th International Conference on Spoken Language Processing, ICSLP 2002 |
|---|---|
| 国 | United States |
| 市 | Denver |
| 期間 | 02/9/16 → 02/9/20 |
Fingerprint
ASJC Scopus subject areas
- Language and Linguistics
- Linguistics and Language
これを引用
Acoustic-to-articulatory inverse mapping using an HMM-based speech production model. / Hiroya, Sadao; Honda, Masaaki.
7th International Conference on Spoken Language Processing, ICSLP 2002. International Speech Communication Association, 2002. p. 2305-2308.研究成果: Conference contribution
}
TY - GEN
T1 - Acoustic-to-articulatory inverse mapping using an HMM-based speech production model
AU - Hiroya, Sadao
AU - Honda, Masaaki
PY - 2002
Y1 - 2002
N2 - We present a method that determines articulatory movements from speech acoustics using an HMM (Hidden Markov Model)-based speech production model. The model statistically generates speech acoustics and articulatory movements from a given phonemic string. It consists of HMMs of articulatory movements for each phoneme and an articulatory-to-acoustic mapping for each HMM state. For a given speech acoustics, the maximum a posteriori probability estimate of the articulatory parameters of the statistical model is presented. The method's performance on sentences was evaluated by comparing the estimated articulatory parameters with observed parameters. The average rms error of the estimated articulatory parameters was 1.79 mm with phonemic information and 2.16 mm without phonemic information in an utterance.
AB - We present a method that determines articulatory movements from speech acoustics using an HMM (Hidden Markov Model)-based speech production model. The model statistically generates speech acoustics and articulatory movements from a given phonemic string. It consists of HMMs of articulatory movements for each phoneme and an articulatory-to-acoustic mapping for each HMM state. For a given speech acoustics, the maximum a posteriori probability estimate of the articulatory parameters of the statistical model is presented. The method's performance on sentences was evaluated by comparing the estimated articulatory parameters with observed parameters. The average rms error of the estimated articulatory parameters was 1.79 mm with phonemic information and 2.16 mm without phonemic information in an utterance.
UR - http://www.scopus.com/inward/record.url?scp=85009243663&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85009243663&partnerID=8YFLogxK
M3 - Conference contribution
AN - SCOPUS:85009243663
SP - 2305
EP - 2308
BT - 7th International Conference on Spoken Language Processing, ICSLP 2002
PB - International Speech Communication Association
ER -