Selective Gammatone Envelope Feature for Robust Sound Event Recognition
スポンサーリンク
概要
- 論文の詳細を見る
Conventional features for Automatic Speech Recognition and Sound Event Recognition such as Mel-Frequency Cepstral Coefficients (MFCCs) have been shown to perform poorly in noisy conditions. We introduce an auditory feature based on the gammatone filterbank, the Selective Gammatone Envelope Feature (SGEF), for Robust Sound Event Recognition where channel selection and the filterbank envelope is used to reduce the effect of noise for specific noise environments. In the experiments with Hidden Markov Model (HMM) recognizers, we shall show that our feature outperforms MFCCs significantly in four different noisy environments at various signal-to-noise ratios.
著者
-
Kitaoka Norihide
Nagoya Univ.
-
LI Haizhou
Human Language Technology Department, Institute for Infocomm Research, A*STAR
-
TRAN Huy
Human Language Technology Department, Institute for Infocomm Research, A*STAR
-
LENG Yi
Human Language Technology Department, Institute for Infocomm Research, A*STAR
関連論文
- CENSREC-1-C : An evaluation framework for voice activity detection under noisy environments
- AURORA-2J: An Evaluation Framework for Japanese Noisy Speech Recognition(Speech Corpora and Related Topics, Corpus-Based Speech Technologies)
- Evaluation of Combinational Use of Discriminant Analysis-Based Acoustic Feature Transformation and Discriminative Training
- Linear Discriminant Analysis Using a Generalized Mean of Class Covariances and Its Application to Speech Recognition
- Robust Speech Recognition by Combining Short-Term and Long-Term Spectrum Based Position-Dependent CMN with Conventional CMN
- Acoustic Feature Transformation Based on Discriminant Analysis Preserving Local Structure for Speech Recognition
- Noisy Speech Recognition Based on Integration/Selection of Multiple Noise Suppression Methods Using Noise GMMs
- Acoustic Feature Transformation Combining Average and Maximum Classification Error Minimization Criteria
- Driver's irritation detection using speech recognition results (音声・第10回音声言語シンポジウム)
- Driver's irritation detection using speech recognition results (音声言語情報処理)
- Driver's irritation detection using speech recognition results (言語理解とコミュニケーション・第10回音声言語シンポジウム)
- Distant-Talking Speech Recognition Based on Spectral Subtraction by Multi-Channel LMS Algorithm
- Acoustic Model Training Using Pseudo-Speaker Features Generated by MLLR Transformations for Robust Speaker-Independent Speech Recognition
- Selective Gammatone Envelope Feature for Robust Sound Event Recognition
- CENSREC-4: An evaluation framework for distant-talking speech recognition in reverberant environments
- Selective Gammatone Envelope Feature for Robust Sound Event Recognition
- A Graph-Based Spoken Dialog Strategy Utilizing Multiple Understanding Hypotheses
- Acoustic Model Training Using Pseudo-Speaker Features Generated by MLLR Transformations for Robust Speaker-Independent Speech Recognition