For speech-to-text, choose lossless audio when your recording setup and the specific AI endpoint support it. Google Cloud recommends FLAC or LINEAR16: FLAC preserves the original digital samples in a compressed file, while LINEAR16 is uncompressed PCM. If bandwidth requires lossy audio, use a codec accepted by your endpoint and recognize that compression can reduce recognition accuracy, especially when background noise is present. A clear, unclipped recording still matters as much as the format.
What lossless and lossy mean for speech recordings
Lossless audio can be decoded to reproduce the original digital samples. FLAC is lossless compression; LINEAR16 is uncompressed 16-bit signed PCM. Lossy codecs reduce or discard some audio information to make files smaller, so the decoded recording no longer matches the original samples exactly.
Google Cloud warns that lossy formats may reduce speech-recognition accuracy, particularly when background noise is present. That is provider guidance, not a quantified result for every codec or voice-AI model: no universal codec-by-codec accuracy ranking is established here.
Which format should you choose?
| Situation | Practical choice | What to know |
|---|---|---|
| You control recording and transmission | FLAC or LINEAR16, if the endpoint accepts it | Google Cloud recommends both as lossless options. |
| You need to reduce transmission size without losing samples | FLAC | Google’s RecognitionConfig reference says FLAC uses about half the bandwidth of LINEAR16. This is approximate guidance; the actual ratio varies with audio and encoding conditions. |
| Bandwidth constraints require lossy compression | Use a codec on the target endpoint’s current accepted-format list | For its own service, Google Cloud recommends AMR_WB or OGG_OPUS, in that preference order, when lossy compression is needed to conserve bandwidth. This is not a general codec comparison. |
| Your existing file uses an unsupported encoding | Transcode to a supported format such as FLAC or LINEAR16, if the endpoint accepts it | Google recommends this for unsupported original encodings. Transcoding cannot restore information discarded when the audio was first recorded or compressed. |
Check the exact service and endpoint before recording or converting: supported containers, codecs, sample rates, and channel layouts differ. For example, Microsoft’s short-audio Speech-to-Text REST endpoint lists 16 kHz mono WAV/PCM and OGG/Opus. That is a compatibility example for that endpoint, not a rule for every Microsoft service or AI transcription tool.
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Do not choose by file extension alone
WAV is a container, not a guarantee about the audio encoding inside it; a WAV file may contain LINEAR16 or MULAW. Google Cloud’s RecognitionConfig documentation notes that WAV and FLAC include headers. If you explicitly set an encoding for either, make sure the request matches the encoding indicated by the file header or the API may reject it.
Match the audio settings to the recording
Use the sample rate and encoding that describe the actual audio. Google Cloud recommends recording at 16,000 Hz or higher when possible, but advises against resampling solely to reach a target rate. Telephony audio commonly has a native rate of 8,000 Hz; send it at that native rate rather than upsampling just to meet a recommendation. Its best-practices guidance was last updated on 2026-09-30.
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For streaming, Google Cloud identifies a 100-millisecond frame as a good trade-off between efficiency and latency. Treat that as guidance for its service, not a universal setting for every streaming API.
- Keep the request’s declared sample rate and encoding consistent with the supplied audio.
- Check whether the endpoint expects mono, separate speaker channels, or another channel arrangement.
- For separately recorded speakers, Google Cloud recommends sending each channel separately. If speakers are already mixed into one channel, send the mix as recorded.
Improve capture quality before changing codecs
A lossless file preserves the samples you captured; it cannot fix distant speech, clipping, distortion, or room noise. Google Cloud recommends a good-quality microphone positioned close to the speaker, especially in a noisy environment. Listen to a sample for distortion or unexpected noise before sending a long recording.
The Tool Desk
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- Avoid clipping by keeping the input level within range.
- For Google Cloud’s stated recommendations, disable automatic gain control and noise-reduction processing.
- Keep the microphone close enough to capture clear speech, while avoiding handling noise or other unwanted sound.
A USB microphone can help you capture speech close to the source, but no particular model is established as improving recognition. Microphone placement, recording conditions, codec choice, and endpoint compatibility are separate considerations.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.A quick decision checklist
- Identify the endpoint. Check its current accepted containers, codecs, sample rates, and channel requirements.
- Choose lossless if supported. Use FLAC when compressed, lossless transmission is useful, or LINEAR16 when uncompressed PCM suits your workflow.
- Keep native settings where appropriate. Avoid needless resampling, and make the API configuration match the audio’s actual rate and encoding.
- Use lossy audio only when needed. Select an accepted codec based on the endpoint’s guidance, not on a universal ranking.
- Check the capture. Listen for noise or distortion and improve microphone distance and input level before changing formats.
Google Cloud’s Best practices documentation states: “Use a lossless codec to record and transmit audio. FLAC or LINEAR16 is recommended.” The advice is specific to its Speech-to-Text service.
Quick Recap
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