[go: up one dir, main page]

Hendriks et al., 2007 - Google Patents

DFT domain subspace based noise tracking for speech enhancement.

Hendriks et al., 2007

View PDF
Document ID
1589136635153368242
Author
Hendriks R
Jensen J
Heusdens R
Publication year
Publication venue
Interspeech

External Links

Snippet

Most DFT domain based speech enhancement methods are dependent on an estimate of the noise power spectral density (PSD). For non-stationary noise sources it is desirable to estimate the noise PSD also in spectral regions where speech is present. In this paper a …
Continue reading at www.academia.edu (PDF) (other versions)

Classifications

    • GPHYSICS
    • G10MUSICAL INSTRUMENTS; ACOUSTICS
    • G10LSPEECH ANALYSIS OR SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING; SPEECH OR AUDIO CODING OR DECODING
    • G10L21/00Processing of the speech or voice signal to produce another audible or non-audible signal, e.g. visual or tactile, in order to modify its quality or its intelligibility
    • G10L21/02Speech enhancement, e.g. noise reduction or echo cancellation
    • G10L21/0208Noise filtering
    • G10L21/0216Noise filtering characterised by the method used for estimating noise
    • G10L21/0232Processing in the frequency domain
    • GPHYSICS
    • G10MUSICAL INSTRUMENTS; ACOUSTICS
    • G10LSPEECH ANALYSIS OR SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING; SPEECH OR AUDIO CODING OR DECODING
    • G10L21/00Processing of the speech or voice signal to produce another audible or non-audible signal, e.g. visual or tactile, in order to modify its quality or its intelligibility
    • G10L21/02Speech enhancement, e.g. noise reduction or echo cancellation
    • G10L21/0208Noise filtering
    • G10L21/0216Noise filtering characterised by the method used for estimating noise
    • G10L2021/02161Number of inputs available containing the signal or the noise to be suppressed
    • GPHYSICS
    • G10MUSICAL INSTRUMENTS; ACOUSTICS
    • G10LSPEECH ANALYSIS OR SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING; SPEECH OR AUDIO CODING OR DECODING
    • G10L25/00Speech or voice analysis techniques not restricted to a single one of groups G10L15/00-G10L21/00
    • G10L25/03Speech or voice analysis techniques not restricted to a single one of groups G10L15/00-G10L21/00 characterised by the type of extracted parameters
    • G10L25/09Speech or voice analysis techniques not restricted to a single one of groups G10L15/00-G10L21/00 characterised by the type of extracted parameters the extracted parameters being zero crossing rates
    • GPHYSICS
    • G10MUSICAL INSTRUMENTS; ACOUSTICS
    • G10LSPEECH ANALYSIS OR SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING; SPEECH OR AUDIO CODING OR DECODING
    • G10L25/00Speech or voice analysis techniques not restricted to a single one of groups G10L15/00-G10L21/00
    • G10L25/93Discriminating between voiced and unvoiced parts of speech signals
    • GPHYSICS
    • G10MUSICAL INSTRUMENTS; ACOUSTICS
    • G10LSPEECH ANALYSIS OR SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING; SPEECH OR AUDIO CODING OR DECODING
    • G10L25/00Speech or voice analysis techniques not restricted to a single one of groups G10L15/00-G10L21/00
    • G10L25/03Speech or voice analysis techniques not restricted to a single one of groups G10L15/00-G10L21/00 characterised by the type of extracted parameters
    • G10L25/18Speech or voice analysis techniques not restricted to a single one of groups G10L15/00-G10L21/00 characterised by the type of extracted parameters the extracted parameters being spectral information of each sub-band
    • GPHYSICS
    • G10MUSICAL INSTRUMENTS; ACOUSTICS
    • G10LSPEECH ANALYSIS OR SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING; SPEECH OR AUDIO CODING OR DECODING
    • G10L25/00Speech or voice analysis techniques not restricted to a single one of groups G10L15/00-G10L21/00
    • G10L25/03Speech or voice analysis techniques not restricted to a single one of groups G10L15/00-G10L21/00 characterised by the type of extracted parameters
    • G10L25/06Speech or voice analysis techniques not restricted to a single one of groups G10L15/00-G10L21/00 characterised by the type of extracted parameters the extracted parameters being correlation coefficients
    • GPHYSICS
    • G10MUSICAL INSTRUMENTS; ACOUSTICS
    • G10LSPEECH ANALYSIS OR SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING; SPEECH OR AUDIO CODING OR DECODING
    • G10L25/00Speech or voice analysis techniques not restricted to a single one of groups G10L15/00-G10L21/00
    • G10L25/90Pitch determination of speech signals
    • GPHYSICS
    • G10MUSICAL INSTRUMENTS; ACOUSTICS
    • G10LSPEECH ANALYSIS OR SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING; SPEECH OR AUDIO CODING OR DECODING
    • G10L25/00Speech or voice analysis techniques not restricted to a single one of groups G10L15/00-G10L21/00
    • G10L25/78Detection of presence or absence of voice signals
    • GPHYSICS
    • G10MUSICAL INSTRUMENTS; ACOUSTICS
    • G10LSPEECH ANALYSIS OR SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING; SPEECH OR AUDIO CODING OR DECODING
    • G10L19/00Speech or audio signal analysis-synthesis techniques for redundancy reduction, e.g. in vocoders; Coding or decoding of speech or audio signal, using source filter models or psychoacoustic analysis
    • G10L19/04Speech or audio signal analysis-synthesis techniques for redundancy reduction, e.g. in vocoders; Coding or decoding of speech or audio signal, using source filter models or psychoacoustic analysis using predictive techniques
    • G10L19/08Determination or coding of the excitation function; Determination or coding of the long-term prediction parameters
    • GPHYSICS
    • G10MUSICAL INSTRUMENTS; ACOUSTICS
    • G10LSPEECH ANALYSIS OR SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING; SPEECH OR AUDIO CODING OR DECODING
    • G10L15/00Speech recognition
    • G10L15/06Creation of reference templates; Training of speech recognition systems, e.g. adaptation to the characteristics of the speaker's voice
    • G10L15/063Training
    • G10L2015/0635Training updating or merging of old and new templates; Mean values; Weighting
    • G10L2015/0636Threshold criteria for the updating

Similar Documents

Publication Publication Date Title
Hendriks et al. Noise tracking using DFT domain subspace decompositions
Taghia et al. An evaluation of noise power spectral density estimation algorithms in adverse acoustic environments
Cohen Relaxed statistical model for speech enhancement and a priori SNR estimation
KR100330230B1 (en) Noise suppression for low bitrate speech coder
Eaton et al. Noise-robust reverberation time estimation using spectral decay distributions with reduced computational cost
Suh et al. Multiple acoustic model-based discriminative likelihood ratio weighting for voice activity detection
Fraser et al. Multiple window spectrogram and time-frequency distributions
Li et al. Non-stationary noise power spectral density estimation based on regional statistics
Jaramillo et al. A study on how pre-whitening influences fundamental frequency estimation
Hendriks et al. DFT domain subspace based noise tracking for speech enhancement.
Gerkmann et al. Speech presence probability estimation based on temporal cepstrum smoothing
Batina et al. Noise power spectrum estimation for speech enhancement using an autoregressive model for speech power spectrum dynamics
Bavkar et al. PCA based single channel speech enhancement method for highly noisy environment
Wei et al. A novel prewhitening subspace method for enhancing speech corrupted by colored noise
KR100798056B1 (en) Speech Processing Method for Improving Sound Quality in Highly Negative Noise Environments
Nasr et al. Efficient implementation of adaptive wiener filter for pitch detection from noisy speech signals
Thakare Voice activity detector and noise trackers for speech recognition system in noisy environment
Eaton et al. A comparison of non-intrusive SNR estimation algorithms and the use of mapping functions
Farsi Improvement of minimum tracking in minimum statistics noise estimation method
Tao et al. Single Channel Speech Presence Probability Estimation based on Hybrid Global-Local Information
Hansen et al. Use of objective speech quality measures in selecting effective spectral estimation techniques for speech enhancement
Cohen From volatility modeling of financial time-series to stochastic modeling and enhancement of speech signals
Zavarehei et al. Inter-frame modeling of DFT trajectories of speech and noise for speech enhancement using Kalman filters
Wu et al. A Time Domain Estimation Algorithm for Speech Signal Pitch Period
Zavarehei et al. Speech enhancement using Kalman filters for restoration of short-time DFT trajectories