Abstract: A signal activity detector (SAD) combines at least three decision signals to generate a combined decision signal as input to a hangover addition circuit of the SAD. Each of the decision signals indicating whether or not activity is detected in the input signal according to respective decision criteria. The SAD sends the combined decision signal to the hangover addition circuit to generate a final decision signal of the SAD as to whether or not activity is detected in the input signal.

Abstract: In accordance with an example embodiment of the present invention, disclosed is a method and an apparatus for voice activity detection (VAD). The VAD comprises creating a signal indicative of a primary VAD decision and determining hangover addition. The determination on hangover addition is made in dependence of a short term activity measure and/or a long term activity measure. A signal indicative of a final VAD decision is then created.

Abstract: Background noise estimators and methods are disclosed for estimating background noise in an audio signal. Some methods include obtaining at least one parameter associated with an audio signal segment, such as a frame or part of a frame, based on a first linear prediction gain, calculated as a quotient between a residual signal from a 0th-order linear prediction and a residual signal from a 2nd-order linear prediction for the audio signal segment. A second linear prediction gain is calculated as a quotient between a residual signal from a 2nd-order linear prediction and a residual signal from a 16th-order linear prediction for the audio signal segment. Whether the audio signal segment comprises a pause is determined based at least on the obtained at least one parameter; and a background noise estimate is updated based on the audio signal segment when the audio signal segment comprises a pause.

Abstract: A signal activity detector (SAD) receives, from a hangover addition unit of a different SAD, a final decision signal of the different SAD. The final decision signal indicates a final decision of the different SAD as to whether or not the different SAD detects activity in a received input signal. The SAD combines the final decision signal of the different SAD with a preliminary decision signal of the SAD and sends a result of the combining to a hangover addition unit of the SAD. The preliminary decision signal of the SAD indicates a preliminary decision of the SAD as to whether or not the SAD detects activity in the input signal. The hangover addition unit of the SAD generates a final decision signal of the SAD based on the result of the combining.

Abstract: The invention relates to a background noise estimator and a method therein, for supporting sound activity detection in an audio signal segment. The method comprises reducing a current background noise estimate when the audio signal segment is determined to comprise music and the current background noise estimate exceeds a minimum value. This is to be performed when an energy level of an audio signal segment is more than a threshold higher than a long term minimum energy level, lt_min, which is determined over a plurality of preceding audio signal segments, or, when the energy level of the audio signal segment is less than a threshold higher than lt_min, but no pause is detected in the audio signal segment.

Abstract: Background noise estimators and methods are disclosed for estimating background noise in an audio signal. Some methods include obtaining at least one parameter associated with an audio signal segment, such as a frame or part of a frame, based on a first linear prediction gain, calculated as a quotient between a residual signal from a 0th-order linear prediction and a residual signal from a 2nd-order linear prediction for the audio signal segment. A second linear prediction gain is calculated as a quotient between a residual signal from a 2nd-order linear prediction and a residual signal from a 16th-order linear prediction for the audio signal segment. Whether the audio signal segment comprises a pause is determined based at least on the obtained at least one parameter; and a background noise estimate is updated based on the audio signal segment when the audio signal segment comprises a pause.

Abstract: A signal activity detector (SAD) receives, from a hangover addition unit of a different SAD, a final decision signal of the different SAD. The final decision signal indicates a final decision of the different SAD as to whether or not the different SAD detects activity in a received input signal. The SAD combines the final decision signal of the different SAD with a preliminary decision signal of the SAD and sends a result of the combining to a hangover addition unit of the SAD. The preliminary decision signal of the SAD indicates a preliminary decision of the SAD as to whether or not the SAD detects activity in the input signal. The hangover addition unit of the SAD generates a final decision signal of the SAD based on the result of the combining.

Abstract: The invention relates to a background noise estimator and a method therein, for supporting sound activity detection in an audio signal segment. The method comprises reducing a current background noise estimate when the audio signal segment is determined to comprise music and the current background noise estimate exceeds a minimum value. This is to be performed when an energy level of an audio signal segment is more than a threshold higher than a long term minimum energy level, lt_min, which is determined over a plurality of preceding audio signal segments, or, when the energy level of the audio signal segment is less than a threshold higher than lt_min, but no pause is detected in the audio signal segment.

Abstract: The embodiments of the present invention relates to a voice activity detector and a method thereof. The voice activity detector is configured to detect voice activity in a received input signal comprising an input section configured to receive a signal from a primary voice detector of said VAD indicative of a primary VAD decision and at least one signal from at least one external VAD indicative of a voice activity decision from the at least one external VAD, a processor configured to combine the voice activity decisions indicated in the received signals to generate a modified primary VAD decision, and an output section configured to send the modified primary VAD decision to a hangover addition unit of said VAD.

Abstract: The invention relates to a background noise estimator and a method therein, for supporting sound activity detection in an audio signal segment. The method comprises reducing a current background noise estimate when the audio signal segment is determined to comprise music and the current background noise estimate exceeds a minimum value. This is to be performed when an energy level of an audio signal segment is more than a threshold higher than a long term minimum energy level, lt_min, which is determined over a plurality of preceding audio signal segments, or, when the energy level of the audio signal segment is less than a threshold higher than lt_min, but no pause is detected in the audio signal segment.

Abstract: The present invention relates to a voice detector being responsive to an input signal being divided into sub-signals representing a frequency sub-band, comprising: means to calculate, for each sub-band, an SNR value snr[n] based on a corresponding sub-signal for each sub-band and a background signal for each sub-band. The voice detector further comprises: means to calculate a power SNR value for each sub-band, wherein at least one of said power SNR values is calculated based on a non-linear function, means to form a single value snr_sum based on the calculated power SNR values, and means to compare said single value snr_sum and a given threshold value vad_thr to make a voice activity decision vad_prim presented on an output port. The invention also relates to a voice activity detector, a node and a method for selectively suppressing sub-bands in a voice detector.

Abstract: The invention relates to a background noise estimator and a method therein, for supporting sound activity detection in an audio signal segment. The method comprises reducing a current background noise estimate when the audio signal segment is determined to comprise music and the current background noise estimate exceeds a minimum value. This is to be performed when an energy level of an audio signal segment is more than a threshold higher than a long term minimum energy level, lt_min, which is determined over a plurality of preceding audio signal segments, or, when the energy level of the audio signal segment is less than a threshold higher than lt_min, but no pause is detected in the audio signal segment.

Abstract: Background noise estimators and methods are disclosed for estimating background noise in an audio signal. Some methods include obtaining at least one parameter associated with an audio signal segment, such as a frame or part of a frame, based on a first linear prediction gain, calculated as a quotient between a residual signal from a 0th-order linear prediction and a residual signal from a 2nd-order linear prediction for the audio signal segment. A second linear prediction gain is calculated as a quotient between a residual signal from a 2nd-order linear prediction and a residual signal from a 16th-order linear prediction for the audio signal segment. Whether the audio signal segment comprises a pause is determined based at least on the obtained at least one parameter; and a background noise estimate is updated based on the audio signal segment when the audio signal segment comprises a pause.

Abstract: In accordance with an example embodiment of the present invention, disclosed is a method and an apparatus for voice activity detection (VAD). The VAD comprises creating a signal indicative of a primary VAD decision and determining hangover addition. The determination on hangover addition is made in dependence of a short term activity measure and/or a long term activity measure. A signal indicative of a final VAD decision is then created.

Abstract: Voice activity detectors and related methods are provided. Methods include receiving a frame of the input signal; determining a first SNR of the received frame; comparing the determined first SNR with an adaptive threshold; and detecting whether the received frame comprises voice based on the comparison. The adaptive threshold is at least based on total noise energy of a noise level, an estimate of a second SNR and on energy variation between different frames.

Abstract: The invention relates to a background noise estimator and a method therein, for supporting sound activity detection in an audio signal segment. The method comprises reducing a current background noise estimate when the audio signal segment is determined to comprise music and the current background noise estimate exceeds a minimum value. This is to be performed when an energy level of an audio signal segment is more than a threshold higher than a long term minimum energy level, lt_min, which is determined over a plurality of preceding audio signal segments, or, when the energy level of the audio signal segment is less than a threshold higher than lt_min, but no pause is detected in the audio signal segment.

Abstract: In accordance with an example embodiment of the present invention, disclosed is a method and an apparatus for voice activity detection (VAD). The VAD comprises creating a signal indicative of a primary VAD decision and determining hangover addition. The determination on hangover addition is made in dependence of a short term activity measure and/or a long term activity measure. A signal indicative of a final VAD decision is then created.

Abstract: The present invention relates to a method and a background estimator in voice activity detector for updating a background noise estimate for an input signal. The input signal for a current frame is received and it is determined whether the current frame of the input signal comprises non-noise. Further, an additional determination is performed whether the current frame of the non-noise input comprises noise by analyzing characteristics at least related to correlation and energy level of the input signal, and background noise estimate is updated if it is determined that the current frame comprises noise.

Abstract: Voice activity detectors and related methods are provided. Methods include receiving a frame of the input signal; determining a first SNR of the received frame; comparing the determined first SNR with an adaptive threshold; and detecting whether the received frame comprises voice based on the comparison. The adaptive threshold is at least based on total noise energy of a noise level, an estimate of a second SNR and on energy variation between different frames.

Abstract: The invention relates to the technical field of audio encoding and/or decoding technologies, and thus concerns an overall encoding procedure and associated decoding procedure. The encoding procedure involves at least two signal encoding processes (S1-S3) operating on signal representations of a set of audio input channels, as well as residual encoding (S7-S8). It also involves a dedicated process (S4-S6) to estimate and encode energies of the audio input channels. Each encoding process is associated with a corresponding decoding process. In the overall decoding procedure the decoded signals from each encoding process are preferably combined such that the output channels are close to the input channels in terms of energy and/or quality. Normally, the combination step also adapts to the possible loss of one or more signal representation in part or in whole, such that the energy and quality is optimized with the signals at hand in the decoder. In this way, the overall quality of the output channels is improved.