Abstract: Efficient Context Classification and Gated Loudness Estimation The present document relates to methods and systems for encoding an audio signal. The method comprises determining a spectral representation of the audio signal. The determining a spectral representation step may comprise determining modified discrete cosine transform, MDCT, coefficients, or a Quadrature Mirror Filter, QMF, filter bank representation of the audio signal. The method further comprises encoding the audio signal using the determined spectral representation; and classifying parts of the audio signal to be speech or non-speech based on the determined spectral representation. Finally, a loudness measure for the audio signal based on the speech parts is determined.

Abstract: The present document relates to audio forensics, notably the blind detection of traces of parametric audio encoding/decoding. In particular, the present document relates to the detection of parametric frequency extension audio coding, such as spectral band replication (SBR) or spectral extension (SPX), from uncompressed waveforms such as PCM (pulse code modulation) encoded waveforms. A method for detecting frequency extension coding history in a time domain audio signal is described.

Abstract: The invention discloses a method and an encoder for processing a digital audio stereo signal. A digital audio encoder for coding such audio signal comprises a predictive Temporal Noise Shaping (TNS) filter, a Mid-/Side (M/S) coding unit, a control unit for determining a first prediction gain related to the unmodified L/R signal processed by the TNS filter and for determining a second prediction gain related to the M/S-coded L/R signal processed by the TNS filter, wherein the control unit is adapted to disable TNS-filtering—i.e. to bypass the TNS filter—for a current signal frame, if the first and second prediction gains differ by more than a pre-determined mismatch range.

Abstract: The present document relates to audio forensics, notably the blind detection of traces of parametric audio encoding/decoding. In particular, the present document relates to the detection of parametric frequency extension audio coding, such as spectral band replication (SBR) or spectral extension (SPX), from uncompressed waveforms such as PCM (pulse code modulation) encoded waveforms. A method for detecting frequency extension coding history in a time domain audio signal is described.

Abstract: The invention discloses a method and an encoder for processing a digital audio stereo signal. A digital audio encoder for coding such audio signal comprises a predictive Temporal Noise Shaping (TNS) filter, a Mid-/Side (M/S) coding unit, a control unit for determining a first prediction gain related to the unmodified L/R signal processed by the TNS filter and for determining a second prediction gain related to the M/S-coded L/R signal processed by the TNS filter, wherein the control unit is adapted to disable TNS-filtering—i.e. to bypass the TNS filter—for a current signal frame, if the first and second prediction gains differ by more than a pre-determined mismatch range.

Abstract: The present document relates to methods and systems for encoding an audio signal. The method comprises determining a spectral representation of the audio signal. The determining a spectral representation step may comprise determining modified discrete cosine transform, MDCT, coefficients, or a Quadrature Mirror Filter, QMF, filter bank representation of the audio signal. The method further comprises encoding the audio signal using the determined spectral representation; and classifying parts of the audio signal to be speech or non-speech based on the determined spectral representation. Finally, a loudness measure for the audio signal based on the speech parts is determined.