Call transcription
Call transcription is the conversion of spoken audio from a phone conversation into a time-ordered text record of what each participant said.
How call transcription works
Speech recognition processes the incoming audio and produces words, punctuation, and sometimes timestamps or confidence information. A complete call transcript may also identify speaker turns, although assigning speech to the correct participant is a separate problem from recognizing the words themselves. In a live voice system, partial text can support the conversation as it happens, while a finalized transcript can be cleaned up after the call with more context.
Accuracy depends on the source audio and the conversation. Background noise, packet loss, accents, specialized vocabulary, overlapping speech, spelled names, and telephone-band audio can all change the result. A readable transcript can still contain an important error, so it should not automatically be treated as a verbatim legal record or as proof that every detail was understood correctly.
Call transcription is related to call recording but serves a different purpose. A recording preserves audio, including tone and timing. A transcript is searchable and easier for people or software to scan, summarize, classify, and analyze. When a transcript is uncertain, the recording may help a reviewer check the original audio, subject to the organization's recording and retention rules.
Why it matters for AI phone calls
An AI phone agent uses recognized speech to decide how to respond during the call. Afterward, the transcript can support summaries, dispositions, scoring, quality review, and structured data extraction. These downstream uses amplify transcription errors: a misheard date can become an incorrect summary, and a missed negation can reverse a caller's intent.
Teams should test the vocabulary, languages, audio conditions, and caller behaviors they expect in production. Review should focus on business-critical fields rather than only overall readability. Sensitive transcripts also need appropriate access, retention, and deletion controls, because text is easy to search, copy, and send into connected systems.
In practice on ThunderPhone
ThunderPhone phone calls and web widget sessions can produce transcript data. Widget sessions use the same call infrastructure as phone calls and create call-history records.