SPGISpeech consists of 5,000 hours of recorded company earnings calls and their respective transcriptions. The original calls were split into slices ranging from 5 to 15 seconds in length to allow easy training for speech recognition systems. Calls represent a broad cross-section of international business English; SPGISpeech contains approximately 50,000 speakers, one of the largest numbers of any speech corpus, and offers a variety of L1 and L2 English accents. The format of each WAV file is single channel, 16kHz, 16 bit audio.
Transcription text represents the output of several stages of manual post-processing. As such, the text contains polished English orthography following a detailed style guide, including proper casing, punctuation, and denormalized non-standard words such as numbers and acronyms, making SPGISpeech suited for training fully formatted end-to-end models.
Official reference:
O’Neill, P.K., Lavrukhin, V., Majumdar, S., Noroozi, V., Zhang, Y., Kuchaiev, O., Balam, J., Dovzhenko, Y., Freyberg, K., Shulman, M.D., Ginsburg, B., Watanabe, S., & Kucsko, G. (2021). SPGISpeech: 5, 000 hours of transcribed financial audio for fully formatted end-to-end speech recognition. ArXiv, abs/2104.02014.
ArXiv link: https://arxiv.org/abs/2104.02014
| Decoding method | val WER | val CER |
|---|---|---|
| greedy search | 2.40 | 0.99 |
| modified beam search | 2.24 | 0.91 |
| fast beam search | 2.35 | 0.97 |
See RESULTS for details.