تقرير
Building Corpora for Single-Channel Speech Separation Across Multiple Domains
| العنوان: | Building Corpora for Single-Channel Speech Separation Across Multiple Domains |
|---|---|
| المؤلفون: | Maciejewski, Matthew, Sell, Gregory, Garcia-Perera, Leibny Paola, Watanabe, Shinji, Khudanpur, Sanjeev |
| سنة النشر: | 2018 |
| المجموعة: | Computer Science |
| مصطلحات موضوعية: | Computer Science - Computation and Language |
| الوصف: | To date, the bulk of research on single-channel speech separation has been conducted using clean, near-field, read speech, which is not representative of many modern applications. In this work, we develop a procedure for constructing high-quality synthetic overlap datasets, necessary for most deep learning-based separation frameworks. We produced datasets that are more representative of realistic applications using the CHiME-5 and Mixer 6 corpora and evaluate standard methods on this data to demonstrate the shortcomings of current source-separation performance. We also demonstrate the value of a wide variety of data in training robust models that generalize well to multiple conditions. Comment: This work has been submitted to the IEEE for possible publication. Copyright may be transferred without notice, after which this version may no longer be accessible |
| نوع الوثيقة: | Working Paper |
| URL الوصول: | http://arxiv.org/abs/1811.02641 |
| رقم الأكسشن: | edsarx.1811.02641 |
| قاعدة البيانات: | arXiv |
| الوصف غير متاح. |