Guides & Features
Learn about Deepgram's Callback feature, which allows you to have your submitted audio processed asynchronously.
Learn about Deepgram's Diarize feature, which recognizes speaker changes in submitted audio.
Learn about Deepgram's Keyword feature, which allows you to boost or suppress Out-of-vocabulary (OOV) keywords in submitted audio.
Learn about Deepgram's Language feature, which allows you to supply a BCP-47 language tag that hints at the primary spoken language of submitted audio.
Learn about Deepgram's Model feature, which allows you to supply a model to use to process submitted audio.
Learn about Deepgram's Multichannel feature, which transcribes each channel in submitted audio independently.
Named-Entity Recognition (NER)
Learn about Deepgram's Named-Entity Recognition (NER) feature, which recognizes alphanumerics in audio and removes whitespace between the characters in the transcript.
Learn about Deepgram's numerals feature, which converts numbers from written format to numerical format.
Learn about Deepgram's Profanity Filter feature, which looks for recognized profanity and converts it to the nearest recognized non-profane word or removes it from the transcript completely.
Learn about Deepgrams' punctuation feature, which adds punctuation and capitalization to your transcript.
Learn about Deepgram's Redaction feature, which redacts sensitive information, replacing redacted content with asterisks.
Learn about Deepgram's Search feature, which searches for terms or phrases in submitted audio.
Learn about Deepgram's Utterance Split feature, which detects pauses between words in submitted audio. Used when the Utterances feature is enabled for pre-recorded audio.
Learn about Deepgram's Sample Rate feature, which allows you to specify the version of the model you want to use to process your submitted audio.
Learn about Deepgram's utterances feature, which segments speech into meaningful semantic units.