AWS Transcribe

Amazon Transcribe provides transcription services for audio files and audio streams. It uses advanced machine learning technologies to recognize spoken words and transcribe them into text. You can use Amazon Transcribe as a standalone transcription service or add speech-to-text capabilities to any application.

With Amazon Transcribe, you can improve accuracy for your specific use case with language customization, filter content to ensure customer privacy or audience-appropriate language, analyse content in multi-channel audio, partition the speech of individual speakers, and more.

Amazon Transcribe is a robust speech-to-text service that offers a diverse array of features, many of which can be combined between Amazon Transcribe and other AWS services. Examples of what you can do:

• Gain insight into agent-customer calls using Call Analytics. This feature automatically analyses 11 different criteria without any customization on your part. For each speaker, you get sentiment data, talk time, non-talk time, loudness, interruptions, and talk speed.

• Get a summary of customer-agent interactions with call summarization, which provides an at-a-glance summary of issues, action items, and outcomes for every call.

• Teach Amazon Transcribe industry-specific terms, unique spelling, acronyms, and any words that are not being rendered correctly in your transcription results using custom vocabularies. Providing Amazon Transcribe with custom vocabulary can improve the accuracy of your transcription output.

• Create subtitles for your video files. You can also use content redaction (only in US English) and vocabulary filtering when generating subtitles to ensure your content is audience-appropriate. Note that filtered or redacted content shows as white space, ***, or [PII] in your transcript and subtitle files, but the audio itself is not altered.

• Redact personally identifiable information (PII), such as social security numbers, from your transcripts using standard content redaction or Call Analytics sensitive data redaction. Call Analytics can also redact your audio by replacing spoken PII with silence.

• Remove proprietary terms from your transcript using vocabulary filtering. For example, you can mask the name of a new product in a pre-launch stakeholder meeting. Vocabulary filtering can also be used to mask profane, offensive, or audience-inappropriate terms.

If your audio is not in the language you speak, let Amazon Transcribe identify the language for you using language identification. You can then use Amazon Translate to translate your transcript, and have Amazon Polly read your transcript back to you.