Abstract: A plurality of talker embedding vectors may be derived that correspond to a plurality of talkers in an input audio stream. Each talker embedding vector may represent respective voice characteristics of a respective talker. The talker embedding vectors may be generated based on, for example, a pre-enrollment process or a cluster-based embedding vector derivation process. A plurality of instances of a personalized noise suppression model may be executed on the input audio stream. Each instance of the personalized noise suppression model may employ a respective talker embedding vector. A plurality of single-talker audio streams may be generated by the plurality of instances of the personalized noise suppression model. A plurality of single-talker transcriptions may be generated based on the plurality of single-talker audio streams. The plurality of single-talker transcriptions may be merged into a multi-talker output transcription.

Abstract: Joint noise and echo suppression may be performed for enhancing two-way audio communications. Audio data is captured at a communication device and audio data transmitted to the communication device from another communication device are used as input features to a trained machine learning model that uses the transmitted audio data as a reference signal to eliminate residual echo in the captured audio data when also suppressing noise in the captured audio data.

Abstract: A videoconference among a plurality of participants may be hosted, wherein the plurality of participants comprise Internet Protocol (IP)-connected participants and a Public Switched Telephone Network (PSTN)-connected participant. The IP-connected participants may send and receive audio content and video content of the videoconference via IP-based connections. The PSTN-connected participant may send and receive the audio content of the videoconference via a PSTN connection. Additional content from the videoconference may also be transmitted to the PSTN-connected participant, for example as text messages via the PSTN connection. The additional content may include, for example, images of a videoconference screen share, chat posts, polls, and the like. Images may be transmitted in the additional content based on video status change events, such as switching slides or pages in a screen share.

Abstract: Real-time low-complexity stereo speech enhancement with spatial cue preservation may be performed. A stereo speech enhancement system receives a stereo input signal (e.g., a left and right input signal). The stereo speech enhancement system estimates spatial cues for a target speaker and downmixes the stereo input signal into a monaural signal. A low-complexity model may then process the monaural signal to generate an enhanced monaural signal. The stereo speech enhancement system upmixes the enhanced monaural signal based on the estimated spatial cues for the target speaker, to generate an enhanced stereo output signal.