Abstract: A system can dynamically apply compression to data storage for workloads based on how the compression affects the performance for the workloads. The system can track a service level indicator (SLI) during runtime of a workload and dynamically change a level of compression for the workload based on the SLI. The system can track the SLI to increase compression for the workload while maintaining a performance minimum specified in a service level agreement (SLA) for the workload.

Abstract: A system, apparatus, method, and computer program product for a speaking aid. The system including network interface circuitry to receive speech input from a user. The speech input includes a partial sentence with a missing word or the partial sentence with a stuttered word. The system also includes a processor coupled to the network interface circuitry and one or more memory devices coupled to the processor. The one or more memory devices include instructions, that when executed by the processor, cause the system to detect a stutter or pause in the speech input, predict the stuttered word or the missing word, present a predicted word from an n-best list to the user; and if a prompt is received from the user, present a next word from the n-best list until the user speaks a correct word to replace the stutter or the pause.

Abstract: A system, method, apparatus and computer readable medium for hierarchical speech recognition resolution. The method of hierarchical speech recognition resolution on a platform includes receiving a speech stream from a microphone. The speech stream is resolved using a lowest possible level automatic speech recognition (ASR) engine of multi-level ASR engines. The selection of the lowest possible level ASR engine is based on policies defined for the platform. If resolution of the speech stream is rated less than a predetermined confidence level, the resolution of the speech stream is pushed to a next higher-level ASR engine of the multi-level ASR engines until the resolution of the speech stream meets the predetermined confidence level without violating one or more policies.

Abstract: An example apparatus for detecting keywords in audio includes an audio receiver to receive audio comprising a keyword to be detected. The apparatus also includes a spike transducer to convert the audio into a plurality of spikes. The apparatus further includes a spiking neural network to receive one or more of the spikes and generate a spike corresponding to a detected keyword.

Abstract: An example apparatus for detecting keywords in audio includes an audio receiver to receive audio comprising a keyword to be detected. The apparatus also includes a spike transducer to convert the audio into a plurality of spikes. The apparatus further includes a spiking neural network to receive one or more of the spikes and generate a spike corresponding to a detected keyword.

Abstract: A system, apparatus, method, and computer program product for a speaking aid. The system including network interface circuitry to receive speech input from a user. The speech input includes a partial sentence with a missing word or the partial sentence with a stuttered word. The system also includes a processor coupled to the network interface circuitry and one or more memory devices coupled to the processor. The one or more memory devices include instructions, that when executed by the processor, cause the system to detect a stutter or pause in the speech input, predict the stuttered word or the missing word, present a predicted word from an n-best list to the user; and if a prompt is received from the user, present a next word from the n-best list until the user speaks a correct word to replace the stutter or the pause.

Abstract: A system, apparatus, method, and computer readable medium for using an audio trigger for surveillance in a security system. The method including receiving an audio input stream via a microphone. Dividing the audio input stream into audio segments. Filtering high energy audio segments from the audio segments. If a high energy audio segment includes speech, then determining if the speech is recognized as the speech of users of the system. If the high energy audio segment does not include the speech, then classifying the high energy audio segment as an interesting sound or an uninteresting sound. Determining whether to turn video on based on classification of the high energy audio segment as the interesting sound, speech recognition of the speech as the speech of the users of the system, and contextual data.

Abstract: A system, method, apparatus and computer readable medium for hierarchical speech recognition resolution. The method of hierarchical speech recognition resolution on a platform includes receiving a speech stream from a microphone. The speech stream is resolved using a lowest possible level automatic speech recognition (ASR) engine of multi-level ASR engines. The selection of the lowest possible level ASR engine is based on policies defined for the platform. If resolution of the speech stream is rated less than a predetermined confidence level, the resolution of the speech stream is pushed to a next higher-level ASR engine of the multi-level ASR engines until the resolution of the speech stream meets the predetermined confidence level without violating one or more policies.

Abstract: Described herein are systems, methods and apparatus for decoding in-band on-channel signals and extracting audio and data signals. Memory requirements are reduced by selectively filtering a bit stream of data in the signal so that services of interest which are encoded therein are processed. A single pool of memory may be shared between physical layer and data link layer processing. Memory in this pool may be allocated dynamically between processing of data at the physical and data link layers. When the available memory is not sufficient to support the required services, the dynamic allocation allows for graceful degradation.

Abstract: A system, article, and method of environment-sensitive automatic speech recognition.

Abstract: Enhancements to hardware architectures (e.g., a RISC processor or a DSP processor) to accelerate spectral band replication (SBR) processing are described. In some embodiments, instruction extensions configure a reconfigurable processor to accelerate SBR and other audio processing. In addition to the instruction extensions, execution units (e.g., multiplication and accumulation units (MACs)) may operate in parallel to reduce the number of audio processing cycles. Performance may be further enhanced through the use of source and destination units which are configured to work with the execution units and quickly fetch and store source and destination operands.

Abstract: Enhancements to hardware architectures (e.g., a RISC processor or a DSP processor) to accelerate spectral band replication (SBR) processing are described. In some embodiments, instruction extensions configure a reconfigurable processor to accelerate SBR and other audio processing. In addition to the instruction extensions, execution units (e.g., multiplication and accumulation units (MACs)) may operate in parallel to reduce the number of audio processing cycles. Performance may be further enhanced through the use of source and destination units which are configured to work with the execution units and quickly fetch and store source and destination operands.

Abstract: Enhancements to hardware architectures (e.g., a RISC processor or a DSP processor) to accelerate spectral band replication (SBR) processing are described. In some embodiments, instruction extensions configure a reconfigurable processor to accelerate SBR and other audio processing. In addition to the instruction extensions, execution units (e.g., multiplication and accumulation units (MACs)) may operate in parallel to reduce the number of audio processing cycles. Performance may be further enhanced through the use of source and destination units which are configured to work with the execution units and quickly fetch and store source and destination operands.

Abstract: Enhancements to hardware architectures (e.g., a RISC processor or a DSP processor) to accelerate spectral band replication (SBR) processing are described. In some embodiments, instruction extensions configure a reconfigurable processor to accelerat SBR and other audio processing. In addition to the instruction extensions, execution units (e.g., multiplication and accumulation units (MACs)) may operate in parallel to reduce the number of audio processing cycles. Performance may be further enhanced through the use of source and destination units which are configured to work with the execution units and quickly fetch and store source and destination operands.

Abstract: Enhancements to hardware architectures (e.g., a RISC processor or a DSP processor) to accelerate spectral band replication (SBR) processing are described. In some embodiments, instruction extensions configure a reconfigurable processor to accelerat SBR and other audio processing. In addition to the instruction extensions, execution units (e.g., multiplication and accumulation units (MACs)) may operate in parallel to reduce the number of audio processing cycles. Performance may be further enhanced through the use of source and destination units which are configured to work with the execution units and quickly fetch and store source and destination operands.