The Tool Desk
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Start with the task and endpoint
Voice AI can mean speech recognition, realtime audio input, telephony, or text-to-speech output. Their format requirements are not interchangeable. A format listed for a text-to-speech response does not establish that a recognition endpoint accepts it.
- Identify the pipeline stage. Determine whether audio is being sent for recognition, carried through a realtime or telephony connection, or generated by text-to-speech.
- Check the exact endpoint and model documentation. Confirm accepted encodings and sample rates for the request type you will use. Treat defaults and model-specific behavior as implementation details to verify, since APIs can change.
- Match the full representation. Check container, codec or encoding, sample rate, bit depth, channel count, and whether the endpoint expects a complete file or raw streaming data.
- Convert only to meet a stated requirement. Resampling changes the sample rate; transcoding changes the encoding or container. Avoid unnecessary conversion steps that can discard information.
- Test the actual request. Confirm that declared metadata matches the audio, the channel count is accepted, and any streaming framing is correct.
WAV is a container, not a complete format specification
A filename ending in .wav does not, by itself, tell you the encoding, bit depth, or sample rate inside the file. WAV is a container that can hold different audio encodings. Check the file metadata and the receiving service’s requirements rather than relying on the extension.
Google Cloud Speech-to-Text documents WAV with LINEAR16 or μ-law and can infer encoding and sample rate from WAV or FLAC headers when those values are omitted from the request. That behavior is specific to its documented service; do not assume another API handles headers the same way. See the Google Cloud Speech-to-Text encoding guide.
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WAV or MP3: choose according to the job
For recognition input you control, Google recommends lossless FLAC or LINEAR16 and cautions that lossy encoding can affect recognition. This is Google’s guidance for its Speech-to-Text service, not a guarantee that every provider or model behaves identically. If you have an original lossless recording and the endpoint accepts it, avoid converting it to a lossy format first.
MP3 is not automatically wrong: it may be a supported option for a particular endpoint. For example, OpenAI’s cited speech API reference lists MP3, Opus, AAC, FLAC, WAV, and PCM for speech output and gives MP3 as the default. That is an output-format list, not evidence that the same formats are accepted by every OpenAI input endpoint. Check the specific API reference for your use case: OpenAI Audio API reference.
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Choose the sample rate the endpoint requires
There is no universal best rate for voice AI. A service’s supported rate can depend on the model, encoding, and task. Use the rate required or supported by the exact endpoint; do not select 16 kHz, 24 kHz, or 44.1 kHz simply because it is common in another workflow.
Google Cloud Speech-to-Text’s encoding guide illustrates why the encoding matters: it lists AMR at 8 kHz, AMR-WB at 16 kHz, and Opus at 8, 12, 16, 24, or 48 kHz. These are service-specific constraints, not general rules for every voice-AI API.
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When an endpoint requires a different rate from your source, resample to that target rate. Upsampling does not recover detail or frequencies that were absent from the original recording.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.Complete files and streaming chunks are different
A complete audio file can include a header describing its contents; raw streaming chunks may not. If software treats headerless PCM as a WAV file, or blindly concatenates chunks with file headers, the resulting audio can be misframed or invalid.
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Google’s Gemini TTS documentation describes unary output as a complete WAV file with a RIFF header, while streaming output defaults to headerless raw PCM chunks. Its documented default is 24 kHz mono, 16-bit signed little-endian PCM. Code handling the stream must follow the streaming representation rather than assume each chunk is a standalone WAV file. See the Gemini speech generation documentation.
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Provider examples: verify the exact model path
| Service and use | Documented behavior | What to check |
|---|---|---|
| OpenAI speech output | The cited API reference lists MP3, Opus, AAC, FLAC, WAV, and PCM; the default is MP3. | This describes output formats. Check the specific input endpoint separately. OpenAI Audio API reference. |
| Google Gemini TTS | The cited documentation describes unary WAV/PCM output and headerless PCM chunks by default for streaming. The default representation is 24 kHz mono, 16-bit signed little-endian PCM. | Handle complete files and streams according to their distinct framing. Check current model behavior and options. Gemini speech generation documentation. |
| Google Cloud Speech-to-Text | The encoding guide lists LINEAR16, FLAC, MULAW, AMR/AMR-WB, OGG_OPUS, WEBM_OPUS, and other encodings; it specifies rate constraints for some encodings and describes reading encoding and rate from WAV or FLAC headers. | Use the encoding and rate accepted by the recognition request. Google recommends FLAC or LINEAR16 when the source is under your control. Google Cloud Speech-to-Text encoding guide. |
| Google Cloud Gemini Enterprise Agent Platform TTS | The cited overview describes WAV/linear PCM at 24 kHz and μ-law/A-law at 8 kHz for the documented Gemini 3.8 TTS models. It says the sampleRate field is ignored on that path. |
Do not assume an exposed setting is honored by every model. If another rate is needed, the documentation advises client-side resampling. Google Cloud Gemini TTS overview. |
Common mistakes to avoid
- Choosing by extension alone: inspect the encoding and metadata inside WAV or other containers.
- Assuming one rate fits every task: follow the selected endpoint’s constraints.
- Confusing output support with input support: check the API path you actually call.
- Converting repeatedly: retain the source and make only the conversion needed for compatibility.
- Handling streaming bytes as files: confirm whether chunks include headers and how the endpoint frames them.
- Trusting a sample-rate parameter without checking model behavior: documentation for a particular Google Cloud TTS path says that its
sampleRatefield is ignored.
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