A microphone array speech enhancement algorithm based on analysis/synthesis filtering that allows for variable signal distortion. The algorithm is used to suppress additive noise and interference. The processing structure consists of delaying the received signals so that the desired signal components add coherently, filtering each of the delayed signals through an analysis filter bank, summing the corresponding channel outputs from the sensors, applying a gain function to the channel outputs, and combining the weighted channel outputs using a synthesis filter. The structure uses two different gain functions, both of which are based on cross correlations of the channel signals from the two sensors. The first gain yields the GEQ-I array, which performs best for the case of a desired speech signal corrupted by uncorrelated white background noise. The second gain yields the GEQ-II array, which performs best for the case where there are more signals than microphones. The GEQ-II gain allows for a trade-off on a channel-dependent basis of additional signal degradation in exchange for additional noise and interference suppression.

Analysis/synthesis-based microphone array speech enhancer with variable signal distortion

The speech encoding apparatus (220) has a first layer encoding section (2201), a first layer decoding section (2202), a delay section (2203), a subtracting section (104), a frequency domain transforming section (101), a second layer encoding section (105) and a multiplexing section (106).

Encoding device, decoding device, and method thereof

Speech recognition models are dynamically re-configurable based on user information, background information such as background noise and transducer information such as transducer response characteristics to provide users with alternate input modes to keyboard text entry (Fig. 5). The techniques of dynamic re-configurable speech recognition provide for deployment of speech recognition on small devices such as mobile phones and personal digital assistants as well environments such as office, home or vehicle while maintaining the accuracy of the speech recognition.

Systems and methods for dynamic re-configurable speech recognition

Methods and apparatus for transmitting data between different peer-to-peer communication groups (104) are disclosed. A wireless device (102) determines (702) if it is simultaneously connected to a plurality of peer-to-peer communication groups (104) and instantiates (704) a bridge interface (404) at the wireless device (102) for communications between each peer-to-peer communication group (104). The wireless device (102) also determines (706) if it is simultaneously connected to at least one peer-to-peer communication device (102) and an access point (202). In such an instance, the wireless device (102) determines (708) if the access point (202) also includes a bridge interface (412). If the access point (202) does not include a bridge interface, the wireless device (102) runs (710) the bridge interface (404) at the wireless device (102) for communications between the at least one peer-to-peer communication device (102) and the access point (202). If the access point (202) does include a bridge interface (412), the wireless device (102) causes (712) the bridge interface (412) at the access point (202) to be instantiated for communications between the at least one peer-to-peer communication device (102) and the access point (202).

Methods and apparatus for transmitting data between different peer-to-peer communication groups

A voice enhancement logic improves the perceptual quality of a processed voice. The voice enhancement system includes a noise detector and a noise attenuator. The noise detector detects a wind buffet and a continuous noise by modeling the wind buffet. The noise attenuator dampens the wind buffet to improve the intelligibility of an unvoiced, a fully voiced, or a mixed voice segment.

System for Suppressing Wind Noise

A method that can be used not only for elimination of noise, for example in automatic speech recognition, but also to improve the voice quality for people, for instance during use of the speaker function of a car phone. The noise reduction is executed with two or multiple channels in such a manner that the temporal and architectural acoustical signal properties of speech and interference are utilized step-by-step and systematically. According to the method a pivotable, acoustic directional lobe is produced for the individual voice channels by respective digital directional filters and a linear phase estimation to correct for a phase difference between the two channels. The noise in the individual voice channels is estimated during speaking pauses, and the temporally stationary noise sources are damped by means of spectral subtraction. The individual voice channels are subsequently added whereby the statistical disturbances of spectral subtraction are averaged. Finally, the composite signal resulting from the addition is subsequently processed with a modified coherence function to damp diffuse noise and echo components.

Noise-reduction method for noise-affected voice channels

The present invention relates to a method with which speech is captured in a noisy environment with as high a speech quality as possible. To this end, a compact array of, for example, two single microphones is combined to form one system through signal processing methods consisting of adaptive beam formation and spectral subtraction. Through the combination with a spectral subtraction, the reference signal of the beam former is freed from speech signal components to the extent that a reference signal of the interference is formed and the beam former produces high gains.

Noise reduction method with self-controlling interference frequency

Voice command operated systems are being installed in modern motor vehicles with increasing frequency Such systems should be operable by various vehicle occupants and from various seating positions A new type of speech recognition system is described, which is good at accomplishing these tasks Therein, for regulating the speech recognition system, the reception characteristic of a a directionally selective microphone array (12) is controlled by an optimization unit (10) These speech signals are then processed in a speech recognizer (11) at least parallel in time Then, on the basis of the results provided by the speech recognizer (11), the reception characteristic of the microphone array (12) is so controlled by an optimization unit (10), that the recognition performance of the speech recognizer (11) downstream of the optimization unit (10) is optimized Herein, the speech recognizer is supplied with the received speech signals from different spatial directions parallel or at least quasi-parallel via the speech channels (14), so that this selects and further processes those speech signals that have the potential for the best possible recognition performance On the basis of the recognition results, the optimization unit (10) obtains via the speech recognizer the necessary regulatory signals (18), in order to optimize the reception characteristics of the microphone array (12) by means of the optimization unit (10) with regard to the respective direction from which speech signals are received, which have the potential for the best possible recognition performance

Intelligent acoustic microphone fronted with speech recognizing feedback

The invention concerns a method of reducing voice signal interference using a noise-reducing method. According to the invention, a masking curve is determined both for the input signal and the output signal of the noise reduction. By comparing the signal portions exceeding the respective masking curve, newly audible portions can be detected in the form of interference in the output signal, according to the type of musical tone, and subsequently damped selectively.

Method of reducing voice signal interference

A method for reducing interference in acoustic signals by using of an adaptive filter method involving spectral subtraction. The inventive method enables a significant reduction of interference in acoustic signals, especially voice signals, without causing any substantial falsification of said signals such as echo or musical tones, and significantly reduces computational requirements in comparison with other methods known per se that are similarly designed to improve signal quality.

Klaus Linhard

Papers

Noise-reduction method for noise-affected voice channels

Noise reduction method with self-controlling interference frequency

Intelligent acoustic microphone fronted with speech recognizing feedback

Method of reducing voice signal interference

Method for reducing interference in acoustic signals using an adaptive filtering method involving spectral subtraction