If voice AI clips words, sounds distorted, misunderstands speech, or repeats its own audio, first find out whether the problem is in the recording or introduced later. Play back a short recording, then check microphone placement and input level, confirm the exact audio format required by your service, and test processing settings one at a time. If speech remains ambiguous, configure the agent to ask for clarification rather than guess.
First, determine where the audio problem starts
Listen to the recording before changing the AI settings
Record a short sample and play it back. If it already sounds harsh, clipped, noisy, or unclear, focus first on the microphone, its position, input level, room noise, and device settings. Google recommends this record-and-playback check in its Gemini Live troubleshooting guidance.
If the recording sounds clean but the voice AI receives garbled, unusually fast, slow, or pitched audio, check the stream format and the service’s configuration. A downstream model cannot reliably restore speech detail that was lost when the original signal clipped.
Prevent clipping at the microphone
Adjust position and input level
Move the microphone closer to the speaker where practical, then reduce excessive input gain if loud words sound flattened or harsh. This helps avoid clipping in the captured signal; software should not be expected to reconstruct peaks that were cut off.
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Google Assistant SDK guidance suggests peak speech levels of approximately -20 to -10 dBFS and recommends a 16,000 Hz source rate if possible, otherwise matching the source’s native rate. These are Google Assistant-specific recommendations, not universal targets for every device or voice service. See Google Assistant SDK audio best practices.
That guidance says: “For best results, position the microphone close to the user, avoid clipping, disable automatic gain control and all noise reduction processing.” Apply that recommendation to Google Assistant SDK speech input; other services may recommend different processing.
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Match the audio format to the selected service
Verify sample rate, encoding, and channels
A mismatch between the actual audio stream and the format declared to the service can make speech sound garbled, too fast, too slow, or pitched incorrectly. Check the current documentation for the exact API and make the captured stream match its requirements; do not assume one provider’s settings apply to another.
| Service documentation | Format example | Practical implication |
|---|---|---|
| AssemblyAI Voice Agent API troubleshooting | PCM16, mono, 24,000 Hz | Use this format for the documented API example; wrong sample-rate handling can produce garbled or wrong-speed audio. |
| Google Gemini Live troubleshooting | Little-endian 16-bit PCM, 16 kHz, single channel | This is a different service requirement, not an interchangeable default. |
| Google Cloud Speech-to-Text best practices | Request should accurately describe encoding and sample rate | For headerless audio, match the declared sample rate to the native source rate rather than resampling blindly. |
Test noise suppression and gain control deliberately
Change one processor at a time
Noise reduction, automatic gain control (AGC), and echo cancellation may be applied by the microphone, browser, operating system, or voice service. Stacking several processors can make it difficult to identify the source of a change, so test one setting at a time and keep a record of what changed.
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Guidance varies by platform. Google Assistant SDK advises disabling AGC and noise reduction for its speech input. Microsoft Foundry documents configurable near-field, far-field, and deep-noise-suppression modes, as well as echo cancellation when the agent’s output might be picked up by the microphone. Consult the relevant platform documentation before enabling or disabling a processor: Google Assistant SDK audio best practices and Microsoft Foundry voice-agent configuration.
Choose processing for the capture situation
- Near-field headset or handset: Check the service’s near-field options and avoid adding unnecessary processing on top of device or browser processing.
- Far-field speakerphone or room microphone: Consider the service’s far-field or noise-suppression options if room noise is the problem.
- Agent audio leaking back into the mic: Test echo cancellation rather than treating it as ordinary background-noise suppression.
More suppression does not automatically mean better recognition. Compare settings using the same spoken phrases and room conditions, following the selected platform’s guidance.
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Stop the agent from hearing its own voice
Check for speaker-to-microphone feedback
If the transcript includes the agent’s own speech or it repeatedly interrupts itself, check whether loudspeaker output is reaching the microphone. AssemblyAI describes this feedback loop and suggests headphones or browser-based acoustic echo cancellation where available. Microsoft Foundry documents an echo-cancellation configuration for cases where agent output can be picked up by the caller’s microphone.
For ChatGPT Voice interruptions specifically, OpenAI Help Center suggests using headphones, moving to a quieter environment, and enabling Voice Isolation on iPhone. See ChatGPT Voice troubleshooting. These steps are specific to that product and situation.
Best Value
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Make unclear-audio handling safe
When speech is noisy, silent, unintelligible, ambiguous, or partly cut off, the agent should ask a brief clarification question instead of filling in missing words. OpenAI’s Realtime prompting guide explicitly treats partially cut-off input as unclear and advises against inferring what was omitted. This improves behavior when the signal is uncertain; it does not repair the audio itself.
Validate changes with repeatable tests
Change one setting at a time and compare recordings or test scenarios made under consistent conditions. Evaluate audio and interaction quality separately from whether the agent completed the underlying task. OpenAI’s voice-agent evaluation guide recommends testing robustness across background noise, microphone quality, room acoustics, and recording conditions. The reviewed guidance does not establish a universal audio-quality score or acceptance threshold.
Quick Recap
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