Nuance Communications, Inc.

Harman Becker Automotive Systems Gmbh

Paragon Ag

Svox Ag

Mohamed Krini

Gerhard Uwe Schmidt

Markus Buck

Bernd Iser

Arthur Wolf

Ingo Schalk-Schupp

Tim Haulick

Shreyas Anand Paranjpe

Tobias Herbig

Franz Gerl

Klaus Rodemer

Raymond Brückner

Patrick B Hannon

Ange Tchinda-Pockem

Martin Rössler

Martin Röβler

Gerhard Schmidt

Patrick Hannon

Jochen Withopf

An arrangement is described for speech signal processing. An input microphone signal is received that includes a speech signal component and a noise component. The microphone signal is transformed into a frequency domain set of short-term spectra signals. Then speech formant components within the spectra signals are estimated based on detecting regions of high energy density in the spectra signals. One or more dynamically adjusted gain factors are applied to the spectra signals to enhance the speech formant components.

Formant dependent speech signal enhancement

A speech signal processing system is described for use with automatic speech recognition and hands free speech communication. A signal pre-processor module transforms an input microphone signal into corresponding speech component signals. A noise suppression module applies noise reduction to the speech component signals to generate noise reduced speech component signals. A speech reconstruction module produces corresponding synthesized speech component signals for distorted speech component signals. A signal combination block adaptively combines the noise reduced speech component signals and the synthesized speech component signals based on signal to noise conditions to generate enhanced speech component signals for automatic speech recognition and hands free speech communication.

Speech enhancement

Embodiments of the present invention exploit redundancy of succeeding FFT spectra and use this redundancy for computing interpolated temporal supporting points. An analysis filter bank converts overlapped sequences of an audio (ex. loudspeaker) signal from a time domain to a frequency domain to obtain a time series of short-time loudspeaker spectra. An interpolator temporally interpolates this time series. The interpolation is fed to an echo canceller, which computes an estimated echo spectrum. A microphone analysis filter bank converts overlapped sequences of an audio microphone signal from the time domain to the frequency domain to obtain a time series of short-time microphone spectra. The estimated echo spectrum is subtracted from the microphone spectrum. Further signal enhancement (filtration) may be applied. A synthesis filter bank converts the filtered microphone spectra to the time domain to generate an echo compensated audio microphone signal. Computational complexity of signal processing systems can, therefore, be reduced.

Temporal interpolation of adjacent spectra

The invention provides a method for estimating a fundamental frequency of a speech signal comprising the steps of receiving a signal spectrum of the speech signal, filtering the signal spectrum to obtain a refined signal spectrum, determining a cross-power spectral density using the refined signal spectrum and the signal spectrum, transforming the cross-power spectral density into the time domain to obtain a cross-correlation function, and estimating the fundamental frequency of the speech signal based on the cross-correlation function.

Method for estimating a fundamental frequency of a speech signal

A system enhances speech by detecting a speaker's utterance through a first microphone positioned a first distance from a source of interference. A second microphone may detect the speaker's utterance at a different position. A monitoring device may estimate the power level of a first microphone signal. A synthesizer may synthesize part of the first microphone signal by processing the second microphone signal. The synthesis may occur when power level is below a predetermined level.

System enhancement of speech signals

A system enhances the quality of a digital speech signal that may include noise. The system identifies vocal expressions that correspond to the digital speech signal. A signal-to-noise ratio of the digital speech signal is measured before a portion of the digital speech signal is synthesized. The selected portion of the digital speech signal may have a signal-to-noise ratio below a predetermined level and the synthesis of the digital speech signal may be based on speaker identification.

Partial speech reconstruction

The present invention relates to a method for signal processing comprising the steps of providing a set of prototype spectral envelopes, providing a set of reference noise prototypes, wherein the reference noise prototypes are obtained from at least a sub-set of the provided set of prototype spectral envelopes, detecting a verbal utterance by at least one microphone to obtain a microphone signal, processing the microphone signal for noise reduction based on the provided reference noise prototypes to obtain an enhanced signal and encoding the enhanced signal based on the provided prototype spectral envelopes to obtain an encoded enhanced signal.

Noise-reduction processing of speech signals

An apparatus processes an acoustic input signal to provide an output signal with reduced noise. The apparatus weights the input signal based on a frequency-dependent weighting function. A frequency-dependent threshold function bounds the weighting function from below.

System for processing an acoustic input signal to provide an output signal with reduced noise

An audio enhancement refines a short-time spectrum. The refinement may reduce overlap between audio sub-bands. The sub-bands are transformed into sub-band short-time spectra. A portion of the spectra are time-delayed. The sub-band short-time spectrum and the time-delayed portion are filtered to obtain a refined sub-band short-time spectrum. The refined spectrum improves audio processing.

Spectral refinement system

A sampling rate conversion system reduces the signal processing burdens carried by cellular phones, headsets, and other electronic devices. Because the system consumes fewer resources to convert between signal sampling rates, the system may significantly reduce processing time and resource requirements in the device. As a result, the device may instead devote resources to performing other useful tasks, such as interacting with the user through a graphical user interface and performing selected processing tasks.

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Ulm, Germany

Mohamed Krini