In this paper, we propose the regression-based packet loss concealment (PLC) for digital speech transmission by using deep neural networks (DNNs) with a multiple-layer deep architecture. For the DNN training, log-power spectra and phases are employed as features in the input layer for the large training set, which ensures non-linear mapping the frames from the last correctly received frame to the missing frame. Once the training is accomplished by the restricted Boltzmann machine (RBM)-based pre-training to initialize the DNN, minimum mean square error (MMSE)-based fine tuning is then performed based on the back-propagation algorithm. In the reconstruction stage, the trained DNN model is fed with the features of the previous frames in order to estimate the log-power spectra and phases of the missing frames. Reconstruction is further improved by using the cross-fading technique to mitigate discontinuity between the reconstruction signal and good frame signal in the time-domain. To demonstrate the performance of the proposed algorithm, hidden Markov model (HMM)-based PLC algorithm and the PLC algorithm standardized in adaptive multi-rate wideband (AMR-WB) Appendix I were used for comparison. The experimental results show that the proposed approach provides better speech quality and speech recognition accuracy than the conventional approaches.

Packet loss concealment based on deep neural networks for digital speech transmission

A technique is described for concealing the effect of a lost frame in a series of frames representing an encoded audio signal in a sub-band predictive coding system. In accordance with the technique, a first synthesized sub-band audio signal is synthesized, wherein synthesizing the first synthesized sub-band audio signal comprises performing waveform extrapolation based on a stored first sub-band decoded audio signal. A second synthesized sub-band audio signal is also synthesized, wherein synthesizing the second synthesized sub-band audio signal comprises performing waveform extrapolation based on the stored second sub-band decoded audio signal. The first synthesized sub-band audio signal and the second synthesized sub-band audio signal are combined to generate a synthesized full-band output audio signal corresponding to a lost frame.

Packet loss concealment for sub-band predictive coding based on extrapolation of sub-band audio waveforms

A technique is described for reducing audible artifacts in an audio output signal generated by decoding a received frame in a series of frames. According to the technique, if the received frame is one of a predefined number of received frames following a lost frame, at least one parameter or signal associated with the decoding of the received frame is altered from a state associated with normal decoding. The received frame is then decoded in accordance with the at least one parameter or signal.

Constrained and controlled decoding after packet loss

A technique is described for use in a decoder configured to decode a series of frames representing an encoded audio signal. The technique is for transitioning between a lost frame and one or more received frames following the lost frame in the series of frames. In accordance with the technique, an output audio signal associated with the lost frame is synthesized. An extrapolated signal is generated based on the synthesized output audio signal. A time lag is calculated between the extrapolated signal and a decoded audio signal associated with the received frame(s), wherein the time lag represents a phase difference between the extrapolated signal and the decoded audio signal. The decoded audio signal is time-warped based on the time lag, wherein time-warping the decoded audio signal comprises stretching or shrinking the decoded audio signal in the time domain.

Time-warping of decoded audio signal after packet loss

A technique is described herein for updating a state of a decoder in a predictive coding system after synthesizing an audio output signal corresponding to a lost frame in a series of frames representing an encoded audio signal. In accordance with the technique, an audio signal associated with the synthesized output audio signal is re-encoded in an encoder to generate an encoder state, wherein the encoder is simplified with respect to an encoder used to generate the encoded audio signal. The state of the decoder is then updated based on the generated encoder state.

Updating of Decoder States After Packet Loss Concealment

This paper presents a candidate for the ITU-T G.722 packet loss concealment standard. The algorithm is based on waveform extrapolation in the speech domain. The strong backward adaptive nature of G.722 makes the state update during lost frames a challenge. The paper presents methods to update the G.722 subband decoder state memory during packet loss. Furthermore, novel techniques to facilitate smooth transition after packet loss are described. Formal subjective test results indicate that the algorithm far exceeds all requirements in the ITU-T terms of reference. Most techniques are applicable to G.726 as well, and some are easily extendable to other speech coders with memory.

A Candidate for the ITU-T G.722 Packet Loss Concealment Standard

This paper describes the BroadVoice® speech coding algorithm, which has been standardized as PacketCable™, SCTE®, and ANSI standards for VoIP cable telephony. The BroadVoice family of codecs includes a 16 kb/s BroadVoice 16 narrowband codec and a 32 kb/s BroadVoice32 wideband codec. BroadVoice is based on two-stage noise feedback coding with vector quantization of excitation and is optimized for low delay, low complexity, and high quality. It has an algorithmic delay of merely 5 ms and a complexity of only 12 and 17 MIPS for BroadVoice16 and BroadVoice32, respectively. The speech quality of BroadVoice16 is better than that of G.728, G.729, and 32 kb/s G.726. The speech quality of BroadVoice32 is better than that of 64 kb/s G.722.

The Broadvoice Speech Coding Algorithm

This paper presents the BroadVoice16 (BV16) speech codec, which is a mandatory codec in the PacketCable 1.5 standard. For cable telephony based on PacketCable 1.5, BV16 possesses a set of attributes not met by other speech codecs: (1) no royalty, (2) high quality, (3) low delay, (4) low complexity, and (5) medium to low bit-rate. The royalty-free requirement excludes many modern speech coding techniques. Hence, an older paradigm is resurrected and improved as the foundation of BV16. Extensive test results including independent subjective tests, PESQ evaluation across 13 languages, and DTMF pass-through evaluation demonstrate the high performance of BV16.

BroadVoice® 16: A PacketCable Speech Coding Standard for Cable Telephony

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A Candidate for the ITU-T G.722 Packet Loss Concealment Standard

The Broadvoice Speech Coding Algorithm

BroadVoice® 16: A PacketCable Speech Coding Standard for Cable Telephony