Microsoft Technology Licensing, LLC

Soren Skak Jensen

Sriram Srinivasan

Koen Bernard Vos

Vinod Prakash

Innovations in phase quantization during speech encoding and phase reconstruction during speech decoding are described. For example, to encode a set of phase values, a speech encoder omits higher-frequency phase values and/or represents at least some of the phase values as a weighted sum of basis functions. Or, as another example, to decode a set of phase values, a speech decoder reconstructs at least some of the phase values using a weighted sum of basis functions and/or reconstructs lower-frequency phase values then uses at least some of the lower-frequency phase values to synthesize higher-frequency phase values. In many cases, the innovations improve the performance of a speech codec in low bitrate scenarios, even when encoded data is delivered over a network that suffers from insufficient bandwidth or transmission quality problems.

Phase reconstruction in a speech decoder

Phase quantization in a speech encoder

Techniques are described for managing synchronized jitter buffers for streaming data (e.g., for real-time audio and/or video communications). A separate jitter buffer can be maintained for each codec. For example, as data is received in network packets, the data is added to the jitter buffer corresponding to the codec that is associated with the received data. When data needs to be read, the same amount of data is read from each of the jitter buffers. In other words, at each instance where data needs to be obtained (e.g., for decoding and playback), the same amount of data is obtained from each of the jitter buffers. In addition, the multiple jitter buffers use the same playout timestamp that is synchronized across the multiple of jitter buffers.

Synchronized jitter buffers to handle codec switches

Techniques are described for performing forward and backward extrapolation of data to compensate for data that has been lost due to network packet loss. The forward and backward extrapolation can be used to perform packet loss concealment. For example, when network packet loss is detected, network packets before and after the lost data can be identified. Forward and backward extrapolation can then be applied to cover the period of lost data. For example, the network packets before the period of lost data can be used to perform forward extrapolation to cover a first portion of the period of lost data. The network packets after the period of lost data can be used to perform backward extrapolation to cover a remaining portion of the period of lost data. The period of lost data can be reconstructed based at least in part on the extrapolation.

Combined forward and backward extrapolation of lost network data

Techniques are described for performing conditional forward error correction (FEC) of network data. The techniques and solutions can be applied to suppress the transmission of redundant forward error correction information for data (e.g., frames of audio and/or video data) that can be effectively recovered at the receiving device (e.g., at the decoder). For example, a first computing device that is encoding and transmitting data (e.g., encoded audio data) to a second computing device can determine whether portions of data can be predicted (e.g., to a certain quality measure) at the second computing device. If the portions of data can be predicted, then the first computing device can skip sending redundant copies of the portions of data (e.g., can skip sending forward error correction information) in current network packets.

Conditional forward error correction for network data

Techniques are described for determining corrected timestamps for streaming data that is encoded using frames with a variable frame size. The streaming data is encoded into frames and transmitted in network packets in which the network packets or frames are associated with timestamps incremented in fixed steps. When a network packet is received after a lost packet, a corrected timestamp range can be calculated for the received packet based at least in part on the received timestamp value and attributes of the received network packet along with buffering characteristics.

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Vancouver, Canada

Soren Skak Jensen