A method that may be used in variety of electronic devices for generating comfort noise includes receiving a plurality of information frames indicative of speech plus background noise, estimating one or more background noise characteristics based on the plurality of information frames, and generating a comfort noise signal based on the one or more background noise characteristics. The method may further include generating a speech signal from the plurality of information frames, and generating an output signal by switching between the comfort noise signal and the speech signal based on a voice activity detection.

Method and apparatus for comfort noise generation in speech communication systems

The spectral domain is efficiently used in order to parameterize the background noise thereby yielding a background noise synthesis which is more realistic and thus leads to a more transparent active to inactive phase switching.

Noise generation in audio codecs

This letter proposes the use of vowel sound detection for voice activity detection. Vowels have distinctive spectral peaks. These are likely to remain higher than their surroundings even after severe corruption. Therefore, by developing a method of detecting the spectral peaks of vowel sounds in corrupted signals, voice activity can be detected as well even in low signal-to-noise ratio (SNR) conditions. Experimental results indicate that the proposed algorithm performs reliably under various noise and low SNR conditions. This method is suitable for mobile environments where the characteristics of noise may not be known in advance.

Robust Voice Activity Detection Using the Spectral Peaks of Vowel Sounds

An apparatus for processing a decoded audio signal (100) comprising a filter (102) for filtering the decoded audio signal to obtain a filtered audio signal (104), a time-spectral converter stage (106) for converting the decoded audio signal and the filtered audio signal into corresponding spectral representations, each spectral representation having a plurality of subband signals, a weighter (108) for performing a frequency selective weighting of the filtered audio signal by a multiplying subband signals by respective weighting coefficients to obtain a weighted filtered audio signal, a subtracter (112) for performing a subband-wise subtraction between the weighted filtered audio signal and the spectral representation of the decoded audio signal, and a spectral-time converter (114) for converting the result audio signal or a signal derived from the result audio signal into a time domain representation to obtain a processed decoded audio signal (116).

Apparatus and method for processing a decoded audio signal in a spectral domain

An apparatus (100) for generating spectral replacement values for an audio signal is provided. The apparatus (100) comprises a buffer unit (110) for storing previous spectral values relating to a previously received error-free audio frame. Moreover, the apparatus (100) comprises a concealment frame generator (120) for generating the spectral replacement values, when a current audio frame has not been received or is erroneous. The previously received error-free audio frame comprises filter information, the filter information having associated a filter stability value indicating a stability of a prediction filter. The concealment frame generator (120) is adapted to generate the spectral replacement values based on the previous spectral values and based on the filter stability value.

Apparatus and method for error concealment in low-delay unified speech and audio coding (usac)

Speech can be modeled as short bursts of vocal energy separated by silence gaps. During typical conversation talk-spurts comprise only 31.5% of each party's speech and the remaining 68.5% is silence. Communication systems can achieve significant gains in spectral efficiency and energy efficiency by disconnecting the users from the spectral resource during the silence periods. This paper develops a simple, efficient, and robust voice activity detection (VAD) algorithm to work in a mobile or portable environment exhibiting dynamically varying background noise. The VAD uses probabilistic distances based on the energy content, the periodicity, the stationarity and the spectral distribution within the low frequency band to decide if the presented speech frame is speech or silence.

H.P. Stern

Papers

A voice activity detection algorithm for communication systems with dynamically varying background acoustic noise