Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: A method of regenerating wideband speech from narrowband speech, the method comprising: receiving samples of a narrowband speech signal having a first range of frequencies; identifying, based on a characteristic of the narrowband speech signal, frequencies in the first range of frequencies to translate into a target band of a regenerated speech signal; modulating the identified frequencies in the first range of frequencies of the received samples of the narrowband speech signal with a modulation signal, the modulation signal having a modulating frequency adapted to upshift the identified frequencies in the first range of frequencies into the target band; filtering the modulated samples, using a target band filter, to form the regenerated speech signal in the target band; and combining the narrowband speech signal with the regenerated speech signal to produce a new wideband speech signal.

Abstract: Network communication speech handling systems are provided herein. In one example, a method of processing audio signals by a network communications handling node is provided. The method includes processing an audio signal to determine a pitch cycle property associated with the audio signal, determining transfer times for encoded segments of the audio signal based at least in part on the pitch cycle property, and transferring packets comprising one or more encoded segments for delivery to a target node in accordance with the transfer time.

Abstract: Network communication speech handling systems are provided herein. In one example, a method of processing audio signals by a network communications handling node is provided. The method includes processing an audio signal to determine a pitch cycle property associated with the audio signal, determining transfer times for encoded segments of the audio signal based at least in part on the pitch cycle property, and transferring packets comprising one or more encoded segments for delivery to a target node in accordance with the transfer time.

Abstract: Network communication speech handling systems are provided herein. In one example, a method of processing audio signals by a network communications handling node is provided. The method includes receiving an incoming excitation signal transferred by a sending endpoint, the incoming excitation signal spanning a first bandwidth portion of audio captured by the sending endpoint. The method also includes identifying a supplemental excitation signal spanning a second bandwidth portion that is generated at least in part based on parameters that accompany the incoming excitation signal, determining a normalized version of the supplemental excitation signal based at least on energy properties of the incoming excitation signal, and merging the incoming excitation signal and the normalized version of the supplemental excitation signal by at least synthesizing an output speech signal having a resultant bandwidth spanning the first bandwidth portion and the second bandwidth portion.

Abstract: A method of regenerating wideband speech from narrowband speech, the method comprising: receiving samples of a narrowband speech signal having a first range of frequencies; identifying, based on a characteristic of the narrowband speech signal, frequencies in the first range of frequencies to translate into a target band of a regenerated speech signal; modulating the identified frequencies in the first range of frequencies of the received samples of the narrowband speech signal with a modulation signal, the modulation signal having a modulating frequency adapted to upshift the identified frequencies in the first range of frequencies into the target band; filtering the modulated samples, using a target band filter, to form the regenerated speech signal in the target band; and combining the narrowband speech signal with the regenerated speech signal to produce a new wideband speech signal.