Speech-to-Text Result Viewer

This is a little tooling around AWS Transcribe to allow us to evaluate the service quality.

See https://speech-to-text.labs.loc.gov/ for the current public release.

Getting Started

1. Have Python 3.7 and Pipenv installed

2. Have your environment configured with the credentials for the AWS account which you intend to use. If you are using multiple accounts, either set AWS_PROFILE or use a tool such as aws-vault to prefix the transcription and download commands.

3. pipenv install --python 3.7

4. Prepare a tab-separated manifest file with the following fields in order:

   • identifier
   • language
   • Title
   • Page to view more information about the file (this will be the more information link)
   • High-quality original master URL (if the URL starts with s3:// it will be passed in directly with no checks; otherwise it will be uploaded to the specified S3 bucket)
   • Streamable audio URL (this will be used by the embedded player)

   Here's an example manifest entry which will be uploaded to S3 before processing:

   afc1941004_sr01    english    "Man-on-the-Street," Washington, D.C., December 8, 1941    https://www.loc.gov/item/afc1941004_sr01/    http://cdn.loc.gov/master/afc/afc1941004/afc1941004_sr01a/afc1941004_sr01a.wav    http://cdn.loc.gov/service/afc/afc1941004/afc1941004_sr01a/afc1941004_sr01a.mp3

   Here's an example manifest entry using a pre-existing S3 object which will be passed directly to Transcribe:

   afc1941004_sr01a	english	"Man-on-the-Street," Washington, D.C., December 8, 1941	https://www.loc.gov/item/afc1941004_sr01/	s3://my-source-bucket/afc/afc1941004/afc1941004_sr01a/afc1941004_sr01a.mp3	https://cdn.loc.gov/service/afc/afc1941004/afc1941004_sr01a/afc1941004_sr01a.mp3

5. Submit the items for transcription. Plese note that this is the point where you will incur charges for the service.

   $ pipenv run python transcribe-items.py my-items.tsv
   Uploading afc1941004_sr01 “"Man-on-the-Street," Washington, D.C., December 8, 1941” to …
   Transcribing afc1941004_sr01 from …
   …

6. Type make to download the results, which may take a number of minutes to become available. The process is repeatable and will not reprocess transcriptions which have already been downloaded.

7. Once at least a single item has been downloaded, you can load the viewer from the local directory (e.g. pipenv run python -m http.server)

8. Uploading to a remote server is as simple as uploading contents of this working directory. make upload will do this once you change the target bucket name for the S3 sync command.