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Register a new userSpectral modification for recognition of children's speech undermismatched conditions
التعديل الطيفي للاعتراف بخطاب الأطفال الظروف المستدامة
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في هذه الورقة، نقترح التعديل الطيفي عن طريق شحذ الأشكال وغير من خلال تقليل الميل الطيفي إلى التعرف على خطاب الأطفال حسب أنظمة التعرف على الكلام التلقائي (ASR) المطورة باستخدام خطاب البالغين.في هذا النوع من الحالة غير المعطاة، يتدهور أداء ASR بسبب عدم التطابق الصوتي واللغوي في السمات بين الأطفال والكبار.يتم استخدام الطريقة المقترحة لتحسين الوضوخي للكلام لتعزيز التعرف على خطاب الأطفال باستخدام نموذج صوتي مدرب على خطاب البالغين.في التجارب، يتم استخدام WSJCAM0 و PFSTAR كقواعد بيانات للبالغين وخطاب الأطفال، على التوالي.تتيح التقنية المقترحة تحسنا كبيرا في سياق ASR القائم على DNN-HMM.علاوة على ذلك، نحن نقوم بالتحقق من صحة متانة التقنية من خلال إظهار أنها تنفذ أيضا في ظروف ضوضاء غير متطابقة.
In this paper, we propose spectral modification by sharpening formants and by reducing the spectral tilt to recognize children's speech by automatic speech recognition (ASR) systems developed using adult speech. In this type of mismatched condition, the ASR performance is degraded due to the acoustic and linguistic mismatch in the attributes between children and adult speakers. The proposed method is used to improve the speech intelligibility to enhance the children's speech recognition using an acoustic model trained on adult speech. In the experiments, WSJCAM0 and PFSTAR are used as databases for adults' and children's speech, respectively. The proposed technique gives a significant improvement in the context of the DNN-HMM-based ASR. Furthermore, we validate the robustness of the technique by showing that it performs well also in mismatched noise conditions.
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If rank A = m = 2 then (١) and (٢) are equalities.
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