When I send to Whisper audio with silence (where nothing is said) it still returns recognized output. Why?
Here is my answer with help from chat to make it better:
Whisper’s core function is converting spoken language into text, and its neural network architecture is specifically trained for this purpose. Think of it like a highly specialized detector that’s always searching for patterns of human speech in audio. When it encounters long stretches of silence, it faces an interesting dilemma - much like how our brains sometimes try to find shapes in clouds, Whisper attempts to interpret the silence through its speech-recognition lens.
This behavior stems from Whisper’s fundamental design assumption that speech is present in the input audio. When no actual speech exists, the model still activates its pattern-matching mechanisms, leading it to generate text from what is essentially noise - a phenomenon known as hallucination in AI systems. This is similar to how a person trained to spot specific patterns might start seeing them even where they don’t exist if they’re looking too hard.
To improve your results, I’d recommend preprocessing your audio files to remove extended periods of silence. This helps Whisper focus on the portions of audio that actually contain speech, reducing the likelihood of these hallucinations. This preprocessing step ensures the model receives input that better matches its training expectations, ultimately leading to more accurate transcriptions.