Abstract: A contact center system for performing call progress analysis including tone and speech classification according to an embodiment includes at least one processor and at least one memory comprising a plurality of instructions stored thereon that, in response to execution by the at least one processor, causes the contact center system to determine a cumulative average of an entropy of an audio signal received by the contact center system, determine a cumulative average power spectral amplitude and a cumulative average spectral entropy of the audio signal, calculate a difference measure of the audio signal as a difference between the cumulative average of the entropy and the cumulative average spectral entropy, distinguish tones from speech of the audio signal based on the difference measure, and process one or more tones of the audio signal in response to identification of the one or more tones in the audio signal.

Abstract: A contact center system for performing call progress analysis including tone and speech classification according to an embodiment includes at least one processor and at least one memory comprising a plurality of instructions stored thereon that, in response to execution by the at least one processor, causes the contact center system to determine a cumulative average of an entropy of an audio signal received by the contact center system, determine a cumulative average power spectral amplitude and a cumulative average spectral entropy of the audio signal, calculate a difference measure of the audio signal as a difference between the cumulative average of the entropy and the cumulative average spectral entropy, distinguish tones from speech of the audio signal based on the difference measure, and process one or more tones of the audio signal in response to identification of the one or more tones in the audio signal.

Abstract: A system and method are presented for unsupervised discovery of similar audio events collected from an automated dialing campaign. Locality Sensitive Hashing (LSH) is used to search for similar audio clips within a large dataset of audio recordings. A database is queried for possible matches between an unknown audio clip and any reference carrier audio message present in the database. The database is updated when new, or changed, carrier audio messages are detected.

Abstract: A system and method are presented for unsupervised discovery of similar audio events collected from an automated dialing campaign. Locality Sensitive Hashing (LSH) is used to search for similar audio clips within a large dataset of audio recordings. A database is queried for possible matches between an unknown audio clip and any reference carrier audio message present in the database. The database is updated when new, or changed, carrier audio messages are detected.

Abstract: A system and method are presented for acoustic echo cancellation. The echo canceller performs reduction of acoustic and hybrid echoes which may arise in a situation such as a long-distance conference call with multiple speakers in varying environments, for example. Echo cancellation, in at least one embodiment, may be based on similarity measurement, statistical determination of echo cancellation parameters from historical values, frequency domain operation, double talk detection, packet loss detection, signal detection, and noise subtraction.

Abstract: A system and method are presented for acoustic echo cancellation. The echo canceller performs reduction of acoustic and hybrid echoes which may arise in a situation such as a long-distance conference call with multiple speakers in varying environments, for example. Echo cancellation, in at least one embodiment, may be based on similarity measurement, statistical determination of echo cancellation parameters from historical values, frequency domain operation, double talk detection, packet loss detection, signal detection, and noise subtraction.

Abstract: A system and method for improving voice recognition processing at a server system that receives voice input from a remotely located user system. The user system includes a microphone, a processor that performs front-end voice recognition processing of the received user voice input, and a communication component configured to send the front-end processed user voice input to a destination wirelessly over a network. The server system includes a communication component configured to receive the sent front-end processed user voice input, and a processor configured to complete voice recognition processing of the sent front-end processed user voice input.

Abstract: A system and method for improving voice recognition processing at a server system that receives voice input from a remotely located user system. The user system includes a microphone, a processor that performs front-end voice recognition processing of the received user voice input, and a communication component configured to send the front-end processed user voice input to a destination wirelessly over a network. The server system includes a communication component configured to receive the sent front-end processed user voice input, and a processor configured to complete voice recognition processing of the sent front-end processed user voice input.

Abstract: A system and method for improving voice recognition processing at a server system that receives voice input from a remotely located user system. The user system includes a microphone, a processor that performs front-end voice recognition processing of the received user voice input, and a communication component configured to send the front-end processed user voice input to a destination wirelessly over a network. The server system includes a communication component configured to receive the sent front-end processed user voice input, and a processor configured to complete voice recognition processing of the sent front-end processed user voice input.

Abstract: A system, method and computer program product for performing speech detection. The method first receives a sound signal and determines if the energy value of the sound signal is above a threshold energy value. If the energy level of the signal is above the threshold energy value, the method determines a predictive signal of the received signal, subtracts the predictive signal from the signal, and determines if the result of the subtraction indicates the presence of speech. If it is determined that no presence of speech is indicated, the threshold energy value is set to the energy level of the present received signal. If it is determined that the result of the subtraction indicates the presence of speech, the received signal is sent to a speech recognition engine. The speech recognition engine generates control system commands for controlling one or more system components. The system components are vehicle system components.

Abstract: A system, method and computer program product for performing speech detection. The method first receives a sound signal and determines if the energy value of the sound signal is above a threshold energy value. If the energy level of the signal is above the threshold energy value, the method determines a predictive signal of the received signal, subtracts the predictive signal from the signal, and determines if the result of the subtraction indicates the presence of speech. If it is determined that no presence of speech is indicated, the threshold energy value is set to the energy level of the present received signal. If it is determined that the result of the subtraction indicates the presence of speech, the received signal is sent to a speech recognition engine. The speech recognition engine generates control system commands for controlling one or more system components. The system components are vehicle system components.

Abstract: A system, method and computer program product for performing noise reduction. The system receives a sound signal determined to include speech, then estimates a noise value of the received sound signal. Next, the system subtracts the estimated noise value from the received signal, generates a prediction signal of the result of the subtraction, and sends the generated prediction signal to a speech recognition engine.

Abstract: A system and method for improving voice recognition processing at a server system that receives voice input from a remotely located user system. The user system includes a microphone, a processor that performs front-end voice recognition processing of the received user voice input, and a communication component configured to send the front-end processed user voice input to a destination wirelessly over a network. The server system includes a communication component configured to receive the sent front-end processed user voice input, and a processor configured to complete voice recognition processing of the sent front-end processed user voice input.