Ch14-Speaker_Recogntion

Ch14-Speaker_Recogntion - Speech Processing Speaker...

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Unformatted text preview: Speech Processing Speaker Recognition February 13, 2012 Veton Kpuska 2 Speaker Recognition Definitions: Speaker Identification: For given a set of models obtained for a number of known speakers, which voice models best characterizes a speaker. Speaker Verification: Decide whether a speaker corresponds to a particular known voice or to some other unknown voice. Claimant an individual who is correctly posing as one of known speakers Impostor unknown speaker who is posing as a known speaker. False Acceptance False Rejection February 13, 2012 Veton Kpuska 3 Speaker Recognition Steps in Speaker Recognition: Model Building For each target speaker (claimant) A number of background (imposter) speakers Speaker-Dependent Features Oral and Nasal tract length and cross section during different sounds Vocal fold mass and shape Location and size of the false vocal folds Accurately measured from the speech waveform. Training Data + Model Building Procedure Generate Models February 13, 2012 Veton Kpuska 4 Speaker Recognition In practice difficult to derive speech anatomy features from the speech waveform. Use conventional methods to extract features: Constant-Q filter bank Spectral Based Features February 13, 2012 Veton Kpuska 5 Speaker Recognition System Feature Extraction Feature Extraction Recognit ion Training Training Speech Data Linda Kay Joe Target & Background Speaker Models Decision: Tom Not Tom Tom Testing Speech Data February 13, 2012 Veton Kpuska 6 Spectral Features for Speaker Recognition Attributes of Human Voice: High-level difficult to extract from speech waveform: Clarity Roughness Magnitude Animation Prosody pitch intonation, articulation rate, and dialect Low-level easy to extract from speech waveform: Vocal tract Spectrum Instantaneous pitch Glottal flow excitation Source Event Onset Times Modulations in Format Trajectories February 13, 2012 Veton Kpuska 7 Spectral Features for Speaker Recognition Want the feature set to reflect the unique characteristics of a speaker. The short-time Fourier transform (STFT): STFT Magnitude: Vocal tract resonances Vocal tract anti-resonances important for speaker identifiability. General trend of the envelope of the STFT Magnitude is influenced by the coarse component of the glottal flow derivative....
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Ch14-Speaker_Recogntion - Speech Processing Speaker...

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