Multi-Assistant Voice Platform for Low-Power Remote Control
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Solution Overview
Problem
Existing remote control devices face challenges with power consumption, network latency, and limited integration with multiple digital assistants, leading to inefficient voice command processing and user inconvenience.
Innovation Solution
Distribute speech recognition between a remote control device and a cloud-based voice platform, utilizing a local processor for trigger word detection and preprocessing, and selecting the appropriate digital assistant based on a trigger word to enhance voice command recognition and reduce power usage.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If voice input is processed locally on the remote control device, then response time is reduced, but power consumption and processing capability requirements increase
Solution Approach 1:
The speech recognition system is segmented into two parts: local trigger word detection on the remote control device and full voice command processing on the cloud-based voice service. This segmentation allows the device to perform only lightweight local processing for trigger detection while sending only necessary data to the cloud, reducing both response time and power consumption compared to full local processing.
Solution Approach 2:
The system performs preliminary action by detecting trigger words locally before sending voice input to the cloud. This preliminary local detection filters out non-trigger speech, allowing the device to remain in a low-power state most of the time while still providing rapid response when a trigger is detected.
2Device complexity
If voice input is sent to cloud-based voice service for processing, then processing capability requirements are reduced, but network consumption and response time increase
Solution Approach 1:
The system extracts only the essential trigger word detection function from the full speech recognition process and keeps it on the device, while sending the extracted trigger detection results and voice input to the cloud for further processing. This extraction minimizes network communication overhead and accelerates response time.
3Adaptability or versatility
If audio responsive remote control is used, then voice command functionality is enabled, but background noise reduces recognition accuracy
Solution Approach 1:
The cloud-based voice service acts as an intermediary that receives the trigger word detection results and original voice input from the remote control device. This intermediary has access to more computational resources and can apply advanced noise filtering and speech recognition algorithms that improve accuracy in noisy environments without increasing device complexity.
4Measurement precision
If faster processor and increased memory are used, then speech recognition accuracy is improved, but power consumption increases
Solution Approach 1:
Instead of implementing full speech recognition capabilities locally, the system performs only the partial action of trigger word detection on the device. This partial processing approach maintains adequate speech recognition accuracy for trigger detection while consuming minimal power, with the understanding that full processing occurs on the cloud.
Data Source
AI summary
Disclosed herein are system, apparatus, article of manufacture, method and/or computer program product embodiments, and/or combinations and sub-combinations thereof, for providing voice control using multiple digital assistants. In some embodiments, a voice platform operates to receive a voice input from a user. The voice platform selects a digital assistant from a plurality of digital assistants based on a trigger word. The voice platform then generates an intent from the voice input using the selected digital assistant. The voice platform then transmits the intent to a media device for processing.