Amazon Transcribe now supports automatic language identification for multi-lingual real-time audio streams

[Amazon Transcribe](https://aws.amazon.com/transcribe/) is an automatic speech recognition (ASR) service that makes it easy for you to add [speech-to-text](https://aws.amazon.com/what-is/speech-to-text/) capabilities to your applications. Today, we are excited to announce automatic language identification support for multi-lingual streams. If you operate in a country with multiple official languages or across multiple regions, your audio streams can contain different languages and switch between languages. For such use cases, you can enable multi-language identification, which identifies all languages spoken in your stream and creates transcript using each identified language. This means that if speakers change languages mid-conversation, or if each participant is speaking a different language, your transcription output detects and transcribes each language correctly. Live streaming transcription is used across industries in contact center applications, broadcast events, meetings captions, and e-learning. With a minimum of 3 seconds of audio, Transcribe can efficiently generate transcripts in the spoken languages without needing humans to specify the language. Automatic language identification for multilingual audio is supported for all [14 languages](https://docs.aws.amazon.com/transcribe/latest/dg/supported-languages.html) that are currently supported for streaming transcriptions at no additional cost, and is available in the following AWS Regions: US East (Ohio), US East (N. Virginia), US West (Oregon), Asia Pacific (Mumbai), Asia Pacific (Singapore), Asia Pacific (Seoul), Asia Pacific (Sydney), Asia Pacific (Tokyo), Africa (Cape Town), Canada (Central), Europe (Frankfurt), Europe (Ireland), Europe (London), South America (São Paulo), and AWS GovCloud (US-East). You can learn more by checking out the Amazon Transcribe [documentation page](https://docs.aws.amazon.com/transcribe/latest/dg/lang-id-stream.html) or visit the [AWS console](https://console.aws.amazon.com/transcribe/) to try it out.