This approach utilizes stereo simultaneous recordings for clean speech and its corresponding noisy speech to compute stereo Gaussian mixture model (GMM).
First we transcribed orthographically the content of the recordings to clean (skipping disfluencies, filled pauses or repairs) and syntactically correct texts.
All recordings were cleaned of potential identifiers.
In this work, we utilize stereo simultaneous recordings for the clean and the corresponding noisy speech in order to train stereo Gaussian mixture model (GMM).
The band also showed disappointment with the ten songs that emerged from the sessions, as Hawkins described the finished tracks as "million-dollar demos", and Grohl considered the recordings "far too clean, too tame and boring".
Finally, we added our own MSO data which address frequency tuning more directly than the MSO studies mentioned, and with intracellular recordings so a clean assessment could be made of the frequency tuning of the monaural inputs (point 3, above).
In particular, the mismatch setting that was employed involves having background database and suspect data from both development and test databases comprised of studio-clean recordings and offender data from both development and test databases comprised of degraded mobile-landline recordings.
The recordings utilized professionally cleaned, air dried, teeth and new dental mirrors and explorers.
Children's observed compliance with a maternal directive was measured by applying a compliance rating system employed by Kochanska et al. [ 51] to the digital recordings of the clean-up task.
Room impulse responses were recorded using this setup and convolved with clean speech recordings used for the evaluation.
