Abstract: A system and method is provided for determining whether a data frame of a coded speech signal corresponds to voice or to noise. In one embodiment, a voice activity detector determines a cross-correlation of data. If the cross-correlation is lower than a predetermined cross-correlation value, then the data frame corresponds to noise. If not, then the voice activity detector determines a periodicity of the cross-correlation and a variance of the periodicity. If the variance is less than a predetermined variance value, then the data frame corresponds to voice. In another embodiment, a method determines energy of the data frame and an average energy of the coded speech signal. If the data frame is one of a predetermined number of initial data frames, then a comparison between the average energy to the energy of the data frame is used to determine whether the data frame is noise or voice.

Abstract: Pitch detection of speech signals finds numerous applications in karaoke, voice recognition and scoring applications. While most of the existing techniques rely on time domain methods, the invention utilizes frequency domain methods. There is provided a method and system for determining the pitch of speech from a speech signal. The method includes the steps of: producing or obtaining the speech signal; distinguishing the speech signal into voiced, unvoiced or silence sections using speech signal energy levels; applying a Fourier Transform to the speech signal and obtaining speech signal parameters; determining peaks of the Fourier transformed speech signal; tracking the speech signal parameters of the determined peaks to select partials; and determining the pitch from the selected partials using a two-way mismatch error calculation.

Abstract: An MPEG-1 layer 3 audio encoder, including a scalefactor generator for determining first scalefactors for encoding a block of audio data if a temporal masking transient is not detected in said block of audio data; and for selecting the maximum of said scalefactors for encoding said block of audio data it a temporal masking transient is detected in said block of audio data to enable greater compression of said audio data. Increases in quantization error, due to use of the maximum scalefactor are pre-masked or post-masked by the temporal masking transient. In cases where the last portion of a block includes a temporal masking transient that masks the preceding portions of the block, the maximum scalefactor is only used to encode the block if the resulting increase in quantization error is less than 30% of the quantization error for the block.