A bandwidth embedding, a small learned vector marking speech as narrowband or wideband, improves narrowband word error rate by 13% relative in a single mixed-bandwidth acoustic model without degrading wideband speech.
As mentioned earlier, for narrowband speech, the spectral features represent information only from 0-4 kHz and the remaining 4-8 kHz are missing
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Bandwidth Embeddings for Mixed-bandwidth Speech Recognition
A bandwidth embedding, a small learned vector marking speech as narrowband or wideband, improves narrowband word error rate by 13% relative in a single mixed-bandwidth acoustic model without degrading wideband speech.