TY - CHAP A1 - Riedhammer, Korbinian A1 - Bocklet, Tobias A1 - Orozco-Arroyave, Juan Rafael A1 - Nöth, Elmar T1 - Semi-Automatic Calibration for Dereverberation by Spectral Subtraction for Continuous Speech Recognition T2 - ITG Symposium on Speech Communication 2014, Erlangen. N2 - In this article, we describe a semi-automatic calibration algorithm for dereverberation by spectral subtraction. We verify the method by a comparison to a manual calibration derived from measured room impulse responses (RIR). We conduct extensive experiments to understand the effect of all involved parameters and to verify values suggested in the literature. The experiments are performed on a text read by 31 speakers and recorded by a headset and three far-field microphones. Results are measured in terms of automatic speech recognition (ASR) performance using a 1-gram model to emphasize acoustic recognition performance. To accommodate for the acoustic change by dereverberation we apply supervised MAP adaptation to the hidden Markov model output probabilities. The combination of dereverberation and adaptation yields a relative improvement of about 35% in terms of word error rate (WER) compared to the original signal. KW - Speech Recognition Y1 - 2014 PB - VDE VERLAG GMBH ER - TY - CHAP A1 - Ghahremani, Pegah A1 - BabaAli, Bagher A1 - Povey, Daniel A1 - Riedhammer, Korbinian A1 - Trmal, Jan A1 - Khudanpur, Sanjeev T1 - A Pitch Extraction Algorithm Tuned for Automatic Speech Recognition T2 - 2014 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Florence, Italy, May 2014. N2 - In this paper we present an algorithm that produces pitch and probability-of-voicing estimates for use as features in automatic speech recognition systems. These features give large performance improvements on tonal languages for ASR systems, and even substantial improvements for non-tonal languages. Our method, which we are calling the Kaldi pitch tracker (because we are adding it to the Kaldi ASR toolkit), is a highly modified version of the getf0 (RAPT) algorithm. Unlike the original getf0 we do not make a hard decision whether any given frame is voiced or unvoiced; instead, we assign a pitch even to unvoiced frames while constraining the pitch trajectory to be continuous. Our algorithm also produces a quantity that can be used as a probability of voicing measure; it is based on the normalized autocorrelation measure that our pitch extractor uses. We present results on data from various languages in the BABEL project, and show a large improvement over systems without tonal features and systems where pitch and POV information was obtained from SAcC or getf0. KW - Automatic Speech Recognition Y1 - 2014 PB - IEEE ER - TY - CHAP A1 - Bocklet, Tobias A1 - Maier, Andreas A1 - Riedhammer, Korbinian A1 - Eysholdt, Ulrich A1 - Nöth, Elmar T1 - Erlangen-CLP: A Large Annotated Corpus of Speech from Children with Cleft Lip and Palate. T2 - Language Resources and Evaluation Conference (LREC), Reykjavik, Iceland, May 2014. N2 - In this paper we describe Erlangen-CLP, a large speech database of children with Cleft Lip and Palate. More than 800 German children with CLP (most of them between 4 and 18 years old) and 380 age matched control speakers spoke the semi-standardized PLAKSS test that consists of words with all German phonemes in different positions. So far 250 CLP speakers were manually transcribed, 120 of these were analyzed by a speech therapist and 27 of them by four additional therapists. The tharapists marked 6 different processes/criteria like pharyngeal backing and hypernasality which typically occur in speech of people with CLP. We present detailed statistics about the the marked processes and the inter-rater agreement. KW - Cleft Lip and palate KW - pathologic speech KW - Children's Speech Y1 - 2014 ER - TY - CHAP A1 - Wegmann, Steven A1 - Faria, Arlo A1 - Janin, Adam A1 - Riedhammer, Korbinian A1 - Morgan, Nelson T1 - The Tao of ATWV: Probing the mysteries of keyword search performance T2 - IEEE Workshop on Automatic Speech Recognition and Understanding (ASRU), Olomouc, Czech Republic, Dezember 2013. N2 - In this paper we apply diagnostic analysis to gain a deeper understanding of the performance of the the keyword search system that we have developed for conversational telephone speech in the IARPA Babel program. We summarize the Babel task, its primary performance metric, “actual term weighted value” (ATWV), and our recognition and keyword search systems. Our analysis uses two new oracle ATWV measures, a bootstrap-based ATWV confidence interval, and includes a study of the underpinnings of the large ATWV gains due to system combination. This analysis quantifies the potential ATWV gains from improving the number of true hits and the overall quality of the detection scores in our system's posting lists. It also shows that system combination improves our systems' ATWV via a small increase in the number of true hits in the posting lists. KW - Speech Recognition Y1 - 2013 ER -