Acoustic Co-Processor Offloading for Speech Recognition

The system divides the speech recognition task into separate functional modules: acoustic modeling (processed by Acoustic Co-Processor), phoneme evaluation (processed by CPU), and word/language modeling (processed by CPU). This segmentation allows the computationally intensive acoustic modeling to be handled separately by a dedicated co-processor, improving overall processing speed while maintaining recognition accuracy through specialized processing at each stage.

An Acoustic Co-Processor is introduced as an intermediary component between the voice signal input and the CPU-based phoneme evaluation. This co-processor acts as a mediator that performs acoustic modeling and generates phoneme scores, which are then passed to the CPU for final recognition. This intermediary architecture offloads computational burden from the CPU, enabling faster processing speeds while preserving accuracy through specialized acoustic analysis.

The acoustic modeling component is extracted from the main CPU-based speech recognition system and placed in a separate Acoustic Co-Processor with dedicated memory. This extraction allows the handheld device to have a smaller main memory footprint while still supporting accurate speech recognition. The co-processor handles the memory-intensive acoustic modeling tasks, freeing up CPU and system memory for other applications, thus enabling portable deployment without sacrificing recognition capability.

Instead of requiring the full speech recognition system to run on the device's limited main memory, the system creates a simplified copy of the critical acoustic modeling functionality in a dedicated co-processor. This co-processor contains a copy of the acoustic model and processing logic, which operates independently from the main CPU memory. This copying approach allows handheld devices with limited memory to support speech recognition without needing to allocate large memory resources to the full system.

The speech recognition processing is segmented into two distinct parts: acoustic modeling handled by the Acoustic Co-Processor and phoneme evaluation handled by the CPU. This segmentation increases processing capability by utilizing dedicated hardware for the most demanding task, while the overall system remains relatively simple as it only adds a single co-processor component rather than requiring complete system redesign.

The Acoustic Co-Processor serves as an intermediary that handles the computationally intensive acoustic modeling tasks, freeing the CPU to focus on phoneme evaluation and higher-level recognition processing. This intermediary architecture enhances overall processing capability by distributing computational workload, while maintaining system simplicity through a clear functional separation between co-processor and CPU responsibilities.