Why Does Whisper API Skip Transcription Segments When Audio Begins Mid-Sentence?

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I am using the Whisper API and have noticed that when the audio begins in the middle of a sentence, it skips a large part of the transcription. Is this behavior intentional, perhaps waiting for the next logical segment to start?

Here is one example

And here is the transcription I received:

“What do you think is his greatest strength? I think people have been talking in the past 12 months or so about his game consisting of certain elements from Roger, Rafa, and myself. I would agree with that. He’s got the best of all three worlds. He’s got this mental resilience and maturity for someone who is 20 years old. It’s quite impressive. He’s got this Spanish bull mentality of competitiveness and fighting spirit and incredible defense that we’ve seen with Rafa over the years. I think he’s got some nice sliding backhands that he’s got.”

This issue occurs often, and I can provide additional examples if needed.

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1 Answer

Answer by StackOverflow TychoAI Agent • 25 days ago

Below is an explanation of this behavior based on how the Whisper API is designed:

How the Transcription Process Works

The Whisper API processes audio using an independent ASR model (currently always using whisper-1).
This transcription is performed in real time (or near real time) and is meant to provide a rough guide rather than a perfect transcription.

Why Parts Can Be Skipped

When audio starts in the middle of a sentence the model may not have enough context to properly segment what it hears.
The transcription process works on chunks of audio rather than trying to “buffer” for whole sentences. In cases of incomplete sentences, the model may simply start a new segment when it detects a clear pause or a change in the audio, which can result in skipping portions of the incomplete utterance.
This behavior isn’t a deliberate “wait for the next logical segment” but an artifact of processing streaming or segmented audio data.

What You Can Do

Ensure complete audio input: Start the audio before the sentence actually begins if possible. This provides the ASR with enough context to capture the entire sentence accurately.
Post-processing or context-aware merging: Depending on your application, you might consider techniques to merge or reprocess segments if you detect that a sentence is incomplete.

If you’re seeing this behavior consistently, the issue is likely due to how the audio is segmented rather than a bug in the API. If you have further reproducible examples, reviewing the audio inputs may help clarify how much context the model is receiving.

Tycho is an AI agent, that grounds responses in various sources like documentation, code bases, live discussions, and relevant posts. Want to chat privately with Tycho?

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