For AI transcription, use lossless audio when your chosen service and endpoint support it: FLAC is compact while preserving the original digital samples, and LINEAR16 is uncompressed PCM. If bandwidth requires lossy audio, follow the endpoint’s accepted formats and capture clean speech; codec choice cannot compensate for clipping, noise, or a microphone placed too far away.
These recommendations are grounded in Google Cloud Speech-to-Text documentation, not a universal comparison across every voice-AI model or recording environment. Endpoint requirements differ, so verify the exact service and API before recording or converting.
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What lossless and lossy mean for a voice recording
Lossless: FLAC preserves the recorded samples
A lossless codec can be decoded back to the original digital audio samples. FLAC compresses audio without discarding sample information, making it a useful option when file size or transmission matters. Google Cloud recommends FLAC for recording and sending audio.
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LINEAR16: uncompressed PCM
LINEAR16 is 16-bit signed pulse-code modulation (PCM), not a compressed lossless codec. It stores the audio without lossy compression, but typically requires more bandwidth than FLAC. Google Cloud estimates FLAC uses about half the bandwidth of LINEAR16; this is approximate guidance, not a guaranteed ratio for every recording.
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Lossy: smaller files, altered audio
Lossy codecs reduce encoded file size by discarding some audio information, so the decoded audio no longer matches the original samples exactly. Google Cloud warns that lossy formats may reduce speech-recognition accuracy, particularly when background noise is present. Its documentation does not quantify the effect for each codec, and that warning should not be read as a universal benchmark for all voice-AI services.
Which format should you choose?
| Situation | Practical choice | Important qualification |
|---|---|---|
| You control the recording and can select a supported format | FLAC or LINEAR16 | Google Cloud recommends both; confirm the specific endpoint accepts the format. |
| File transfer or bandwidth is a concern, but you want to preserve samples | FLAC | Google Cloud describes FLAC as more bandwidth-efficient than LINEAR16, at approximately half the bandwidth. |
| You must use lossy compression to conserve bandwidth | For Google Cloud’s guidance, prefer AMR_WB, then OGG_OPUS. | This ordering is specific to Google Cloud’s best-practices guidance, not a general codec ranking. Use the target endpoint’s current supported-format list. |
| Your existing recording uses a format Google Cloud does not support | Transcode to FLAC or LINEAR16 if the endpoint accepts it. | Transcoding cannot recover audio information already discarded by lossy encoding. |
Do not choose by file extension alone. WAV is a container, and a WAV file can contain different audio encodings, including LINEAR16 or MULAW. Google Cloud’s RecognitionConfig documentation notes that WAV and FLAC include headers; if you explicitly set an encoding for either, make the request match the encoding represented in the header or the API may reject it.
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Endpoint compatibility can vary even within a provider. For example, Microsoft’s short-audio speech-to-text REST endpoint documents 16 kHz mono WAV/PCM and OGG/Opus inputs. Those requirements describe that endpoint, not every Microsoft service or every AI transcription API.
How to keep capture quality high
Match the actual sample rate
Google Cloud recommends a sampling rate of 16,000 Hz or higher when possible, but advises against resampling audio merely 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 solely for compliance. Configure the request to match the audio’s actual sample rate and encoding.
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Record clean, close-positioned speech
Google Cloud recommends a good-quality microphone positioned close to the speaker, especially when there is background noise. Avoid clipping, listen to a sample for distortion or unexpected noise, and follow Google’s recommendations to disable automatic gain control and noise-reduction processing. A USB microphone may help you capture speech from a closer, stable position, but no particular model is established here as improving recognition.
Set streaming frames and channels appropriately
For Google Cloud streaming, a 100-millisecond frame size is described as a good trade-off between efficiency and latency. When speakers have been recorded on separate channels, Google recommends sending each channel separately; if multiple speakers are mixed on one channel, send the recording as it is.
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What codec choice can—and cannot—tell you
For a supported endpoint, lossless capture avoids the additional information loss introduced by lossy encoding. It does not guarantee a more accurate transcript in every case: microphone distance, noise, clipping, sample-rate configuration, channel layout, language, and the model all matter. The cited provider guidance supports using FLAC or LINEAR16 and cautions about lossy audio, but it does not establish a measured accuracy ranking across codecs or across voice-AI providers.
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Use the exact endpoint’s documentation to verify the container, codec, sample rate, and channel requirements before recording or converting. Google Cloud’s Speech-to-Text best practices and audio encoding reference were last updated September 30, 2026.
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