The goal of this article is to show that for some tasks in automatic speech recognition (ASR), especially for recognition of spontaneous telephony speech, the reference annotation differs substantially among human annotators and thus sets the upper bound of the ASR accuracy. In this paper, we focus on the evaluation of the inter-annotator agreement (IAA) and ASR accuracy in the context of imper...

Microstructure evolution, mechanical properties, formability, and texture development were determined for AA6111 samples processed by asymmetric rolling (ASR) with different roll friction, velocity, or diameters, conventional rolling (CR), and equal-channel-angular pressing (ECAP). Highly elongated or sheared grain structures were developed during ASR/CR and ECAP, respectively. ASR led to impro...

In this paper, we test the applicability of state-of-the-art automatic speech recognition (ASR) to predict phoneme confusions in human listeners. Phoneme-specific response rates are obtained from ASR based on deep neural networks (DNNs) and from listening tests with six normal-hearing subjects. The measure for model quality is the correlation of phoneme recognition accuracies obtained in ASR an...

هدف: همان‌گونه که مشهود است، در سازمان‌های خدماتی به‌منظور برندسازی نیاز است ارزش‌های برندشان فعال و نهادینه شود؛ با این پیش‌فرض، پژوهش پیش‌رو هدف استخراج مدل فعال‌سازی برند داخلی از منظر فعالیت‌های مدیریت منابع انسانی تعریف اجرا شده است.طراحی/ روش‌شناسی/ رویکرد: روش مطالعۀ موردی رویکرد کیفی بانک ملت برای توسعۀ پیش گرفته شد. دو مرحلۀ اصلی طراحی گردید مصاحبه‌های عمیق فردی ۱۹ مدیر کارشناس مربوطه ...

In this paper, we introduce a non-linear enhancement technique called Audio-Visual Codebook Dependent Cepstral Normalization (AVCDCN) and we consider its use with both audio-only and audio-visual speech recognition. AVCDCN is inspired from CDCN [1] [2], an audio-only enhancement technique that approximates the non-linear effect of noise on speech with a piece-wise constant function. Our experim...

End-to-end training of automated speech recognition (ASR) systems requires massive data and compute resources. We explore transfer learning based on model adaptation as an approach for training ASR models under constrained GPU memory, throughput and training data. We conduct several systematic experiments adapting a Wav2Letter convolutional neural network originally trained for English ASR to t...

This paper discusses the possibilities to extract features from the speech signal that can be used for the detection of emotional state of the speaker, using the ASR framework. After the introduction, a short overview of the ASR framework is presented. Next, we discuss the relation between recognition of emotion and ASR, and the different approaches found in the literature to tackle the corresp...

High-level speaker-specific features (HLSSFs), such as the style of pronunciation of words, their use, phonotactics and prosody, form the main subjects of state-of-the-art research on automatic speaker recognition (ASR). In this paper, we experimentally verify HLSSF extraction and support vector machine (SVM)-based modelling techniques. The HLSSF extraction produces patterns of symbols for each...

Plasma renin activity (PRA) and aldosterone secretion rate (ASR) were measured in 22 patients in balance on a 100 mEq sodium diet during the malignant phase of hypertension and at intervals during long-term follow-up on pharmacological therapy. Three patients had normal PRA and ASR during malignant hypertension. Eighty-six per cent of patients had an increased ASR, but only in 36% was PRA conco...