Voice conversion through vector quantization.
نویسندگان
چکیده
منابع مشابه
Quality Improvement of Voice Conversion Systems Based on Trellis Structured Vector Quantization
Common voice conversion systems employ a spectral / time domain mapping to convert speech from one speaker to another. The speech quality of conversion methods does not sound natural because the spectral / time domain patterns of two speakers’ speech do not match completely. In this paper we propose a method that uses inter-frame (dynamic) characteristics in addition to intra-frame characterist...
متن کاملHMM-based robust voice conversion using adaptive F0 quantization
This paper proposes an HMM-based voice conversion (VC) technique with quantized F0 symbol context using adaptive F0 quantization. In the HMM-based VC, an input utterance of a source speaker is decoded into phonetic and prosodic symbol sequences, and the converted speech is generated using the decoded information from the pre-trained target speaker’s phonetically and prosodically context-depende...
متن کاملForeign accent conversion through voice morphing
We present a voice morphing strategy that can be used to generate a continuum of accent transformations between a foreign speaker and a native speaker. The approach performs a cepstral decomposition of speech into spectral slope and spectral detail. Accent conversions are then generated by combining the spectral slope of the foreign speaker with a morph of the spectral detail of the native spea...
متن کاملRecognition Of Voice Using Mel Cepstral Coefficient & Vector Quantization
Human Voice is characteristic for an individual. The ability to recognize the speaker by his/her voice can be a valuable biometric tool with enormous commercial as well as academic potential. Commercially, it can be utilized for ensuring secure access to any system. Academically, it can shed light on the speech processing abilities of the brain as well as speech mechanism. In fact, this feature...
متن کاملVertex Data Compression through Vector Quantization
Rendering geometrically detailed 3D models requires the transfer and processing of large amounts of triangle and vertex geometry data. Compressing the geometry bitstream can reduce bandwidth requirements and alleviate transmission bottlenecks. In this paper, we show vector quantization to be an effective compression technique for triangle mesh vertex data. We present predictive vector quantizat...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Journal of the Acoustical Society of Japan (E)
سال: 1990
ISSN: 0388-2861,2185-3509
DOI: 10.1250/ast.11.71