Segment-Based Audio Captioning Queue for Latency Reduction
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Solution Overview
Problem
Current audio captioning systems experience significant latency and inefficiency in transcribing audio signals to text, leading to delayed text display and idle time for communication assistants, which hampers natural conversation flow and increases operational costs.
Innovation Solution
Implementing segment-based queuing for audio captioning, where audio signals are segmented and distributed to multiple communication assistants for simultaneous transcription, reducing latency and idle time by allowing transcription to occur in real-time as segments are received.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If audio signals are processed by a single communication assistant sequentially, then transcription accuracy can be maintained, but latency in text display increases and productivity decreases
Solution Approach 1:
The audio signal is divided into multiple segments that can be processed independently and simultaneously by different communication assistants. This segmentation allows parallel processing, reducing the overall latency while maintaining transcription quality through distributed workload across multiple assistants.
2Device complexity
If audio signals are processed by a single communication assistant sequentially, then system complexity remains low, but productivity and resource utilization decrease
Solution Approach 1:
The audio stream is segmented into manageable chunks that can be distributed to multiple communication assistants. This approach increases productivity by enabling parallel processing while keeping individual assistant tasks simple and manageable, thus not significantly increasing overall system complexity.
Solution Approach 2:
Multiple communication assistants are utilized to perform the same transcription function simultaneously on different audio segments. This multi-functionality approach increases productivity by leveraging multiple resources while maintaining a relatively simple system architecture where each assistant performs a standardized task.
3Productivity
If audio signals are processed by multiple communication assistants in parallel, then latency is reduced and productivity increases, but system complexity and coordination overhead increase
Solution Approach 1:
A queue management system acts as an intermediary between audio input and multiple communication assistants. This mediator coordinates the distribution of audio segments to available assistants, managing the parallel processing workflow and reducing coordination overhead by centralizing the scheduling logic in a single queue management component.
4Measurement precision
If communication assistants wait for complete audio segments before transcription, then transcription accuracy improves, but idle time increases and productivity decreases
Solution Approach 1:
Audio segments are prepared and queued in advance before being assigned to communication assistants. This preliminary action allows assistants to immediately begin transcription work when assigned a segment, minimizing idle time while maintaining accuracy by ensuring segments are fully prepared before transcription begins.
Data Source
AI summary
A method includes receiving an audio signal. The method further includes determining segments of audio from the audio signal. The method further includes sending a first segment of the audio signal to a first communication assistant (CA) device. The method further includes sending a second segment of the audio signal to a second CA device. The method further includes receiving a first text string associated with the first segment from the first CA device. The method further includes sending the first text string to a text display device. The method further includes receiving a second text string associated with the second segment from the second CA device. The method further includes sending the second text string to the text display device.