Dynamic time warping (DTW) and dynamic spectral wafliing (DSW)techniques are introduced into learning vector quantization (LVQ) algorithm to con-struct a “dynamic” Bayes classifier for speech recognition. It can pre...Dynamic time warping (DTW) and dynamic spectral wafliing (DSW)techniques are introduced into learning vector quantization (LVQ) algorithm to con-struct a “dynamic” Bayes classifier for speech recognition. It can preduce highly dis-criminiative “dynamic” reference vectors to represent the temporal and spectral vari-abilities of speech. Recognition experiments on 19 Chinese consonants show that the“dynamic” classifier outperforms the original “static” classifier significantly.展开更多
Side-match vector quantization （SMVQ） achieves better compression performance than vector quantization （VQ） in image coding due to its exploration of the dependence of adjacent pixels. However, SMVQ has the disadv...Side-match vector quantization （SMVQ） achieves better compression performance than vector quantization （VQ） in image coding due to its exploration of the dependence of adjacent pixels. However, SMVQ has the disadvantage of requiring excessive time during the process of coding. Therefore, this paper proposes a fast image coding algorithm using indirect-index codebook based on SMVQ （IIC-SMVQ） to reduce the coding time. Two codebooks, named indirect-index codebook （II-codebook） and entire-state codebook （ES-codebook）, are trained and utilized. The II-codebook is trained by using the Linde-Buzo-Gray （LBG） algorithm from side-match information, while the ES-codebook is generated from the clustered residual blocks on the basis of the II-codebook. According to the relationship between these two codebooks, the codeword in the II-codebook can be regarded as an indicator to construct a fast search path, which guides in quickly determining the state codebook from the ES-codebook to encode the to-be-encoded block. The experimental results confirm that the coding time of the proposed scheme is shorter than that of the previous SMVQ.展开更多
文摘Dynamic time warping (DTW) and dynamic spectral wafliing (DSW)techniques are introduced into learning vector quantization (LVQ) algorithm to con-struct a “dynamic” Bayes classifier for speech recognition. It can preduce highly dis-criminiative “dynamic” reference vectors to represent the temporal and spectral vari-abilities of speech. Recognition experiments on 19 Chinese consonants show that the“dynamic” classifier outperforms the original “static” classifier significantly.
基金supported in part by the National Natural Science Foundation of China under Grant No.61272262
文摘Side-match vector quantization （SMVQ） achieves better compression performance than vector quantization （VQ） in image coding due to its exploration of the dependence of adjacent pixels. However, SMVQ has the disadvantage of requiring excessive time during the process of coding. Therefore, this paper proposes a fast image coding algorithm using indirect-index codebook based on SMVQ （IIC-SMVQ） to reduce the coding time. Two codebooks, named indirect-index codebook （II-codebook） and entire-state codebook （ES-codebook）, are trained and utilized. The II-codebook is trained by using the Linde-Buzo-Gray （LBG） algorithm from side-match information, while the ES-codebook is generated from the clustered residual blocks on the basis of the II-codebook. According to the relationship between these two codebooks, the codeword in the II-codebook can be regarded as an indicator to construct a fast search path, which guides in quickly determining the state codebook from the ES-codebook to encode the to-be-encoded block. The experimental results confirm that the coding time of the proposed scheme is shorter than that of the previous SMVQ.
