Abstract: A speech analyzing stage (12) and a method for analyzing a speech signal is described. The speech analyzing stage (12) is part of an automatic speech recognition system (10) and is adapted for analyzing in the spectral domain a speech signal sampled at one of at least two different system sampling rates. The speech analyzing stage (12) comprises a first spectral analyzer (18a) for analyzing the speech signal up to a first frequency (flowest) which is preferably derived from the lowest system sampling rate (2×flowest) and a second spectral analyzer (18b) for analyzing the speech signal at least above the first frequency (flowest).

Abstract: The present invention relates to a method and an apparatus for a robust feature extraction for speech recognition in a noisy environment, wherein the speech signal is segmented and is characterized by spectral components. The speech signal is splitted into a number of short term spectral components in L subbands, with L=1, 2, . . . and a noise spectrum from segments that only contain noise is estimated. Then a spectral subtraction of the estimated noise spectrum from the corresponding short term spectrum is performed and a probability for each short term spectrum component to contain noise is calculated. Finally these spectral component of each short-term spectrum, having a low probability to contain speech are interpolated in order to smooth those short-term, spectra that only contain noise. With the interpolation the spectral components containing noise are interpolated by reliable spectral speech components that could be found in the neighborhood.

Abstract: A speech analyzing stage (12) and a method for analyzing a speech signal is described. The speech analyzing stage (12 ) is part of an automatic speech recognition system (10) and is adapted for analyzing in the spectral domain a speech signal sampled at one of at least two different system sampling rates.

Abstract: A method and a device for processing distorted short-term speech spectra for automatic speech recognition is described. The method comprises providing a set of reference speech spectra, determining the reference speech spectra of the set of references speech spectra which corresponds to the distorted short-term speech spectra, estimating a frequency response taking into account both the distorted short-term speech spectra and the corresponding reference speech spectra, and compensating the distorted short-term speech spectra based on the estimated frequency response.

Abstract: A mobile terminal (100) controllable by spoken utterances like proper names or keywords is described. The mobile terminal (100) comprises an interface (200) for receiving voice prompts, a model generator (430) for generating acoustic models based on the received voice prompts, and an automatic speech recognizer (110) for recognizing the spoken utterances based on the generated acoustic models.

Abstract: A method for analyzing a spoken sequence of numbers recognized by automatic speech recognition comprises determining the speaking pause length between two consecutive numbers and deciding if the two consecutive numbers belong to a single numerical value on the basis of the determined pause length. A device for analyzing a spoken sequence of numbers comprises an automatic speech recognizer, a unit for determining the pause length between two consecutive numbers and a processing unit for deciding if the two consecutive numbers belong to a single numerical value on the basis of the determined pause length.