TY - CHAP A1 - Jahnke, Thorben Frank A1 - Sonnen, Corinna A1 - Walther, Mathias ED - Baumann, Timo T1 - Konzept und Evaluation eines Softwaresystems zur Unterstützung der CRM-basierten Sprechwirkungsuntersuchung T2 - Elektronische Sprachsignalverarbeitung 2024, Tagungsband der 35. Konferenz, Regensburg, 6.-8. März 2024 N2 - Das Continuous-Response-Measurement-Verfahren bildet durch die kontinuierliche Bewertungsmöglichkeit eine wichtige Ergänzung zu den gängigen Methoden im Repertoire der Wirkungsforschung. Um diesen Mehrwert voll ausschöpfen zu können, wird als Verfahrensoptimierung die Entwicklung einer Softwarelösung vorgestellt. Die Überprüfung des optimierten CRM-Verfahrens erfolgt mittels eines Anwendungsfalls aus der sprechwissenschaftlichen Telekommunikationsforschung im Rahmen eines User-Acceptance-Tests. Dabei wird die Funktionalität und Bedienerfreundlichkeit der entwickelten CRM-Softwarelösung unter Beachtung der für die Sprechwirkungsforschung relevanten Kriterien in Form einer A-BStudie getestet. Das Gesamtergebnis des User-Acceptance-Tests fällt für die Software Evalue positiv aus. Mit Hilfe der Verfahrensoptimierung des CRM-Verfahrens ist eine variabel einsetzbare und damit vielfältig nutzbare CRM-Softwarelösung entstanden. Y1 - 2024 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:898-opus4-70893 SN - 978-3-95908-325-6 SP - 124 EP - 131 PB - TUDpress CY - Dresden ER - TY - CHAP A1 - Venkateswaran, Siddarth A1 - Böck, Ronald ED - Baumann, Timo T1 - Can Language Models Behave Like Wine Sommeliers? – Using Multiple Agents To Evaluate The Quality of Wine Descriptors Generated By Llama 2 T2 - Elektronische Sprachsignalverarbeitung 2024, Tagungsband der 35. Konferenz, Regensburg, 6.-8. März 2024 N2 - Wines are complex beverages whose taste can be described either numerically or textually, with the former involving the rating of the intensities of different aroma characteristics often with the help of a wine tasting wheel, and the latter with the help of crisp terms often in a poetic fashion. These are often done with the help of wine sommeliers who with one sniff can describe the wine. Usually, each sommelier has a unique style when it comes to textually describing a wine, research has shown that such differences have no negative impact in correctly classifying wines on the basis of their color, grape variety, region etc. Given the recent advancements in the field of Natural Language Processing, especially with the emergence of Large Language Models, we aim to check the capability of Llama 2 in its ability to generate texts pertaining to a specific color of a wine, given a list of aroma intensities as input prompts. In our experiments, we relied on data from Meininger and Falstaff, and on a combination of domain adaptation and pseudo-labeling techniques to create the corpus to train the Llama 2 model on. Also, we relied on a voting scheme of three differently trained classifiers to evaluate the wine-color specific text generation capabilities of Llama 2. Additionally, we employed the services of domain experts to evaluate the quality of a sample set of texts that was generated by Llama 2. Y1 - 2024 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:898-opus4-70911 SN - 978-3-95908-325-6 SP - 141 EP - 148 PB - TUDpress CY - Dresden ER - TY - CHAP A1 - Birkholz, Peter A1 - Zhang, Xinyu ED - Baumann, Timo T1 - An Investigation of Acoustic Features of the Lower Vocal Tract for Speaker Recognition T2 - Elektronische Sprachsignalverarbeitung 2024, Tagungsband der 35. Konferenz, Regensburg, 6.-8. März 2024 N2 - Speaker recognition systems often use mel-scaled cepstral coefficients (MFCCs) as main features. In contrast to MFCCs, Godoy et al. (2015) proposed a different type of short-term spectral analysis that provides features related to the lower vocal tract (LVT). They are calculated as the ratio of the acoustic shorttime spectra during the closed and open phases of the glottal oscillation cycles based on a pitch-synchronous analysis. These features were suggested to be particularly speaker-specific and might therefore be suitable to substitute or complement MFCCs in speaker recognition systems. The present study investigated the benefit of these features in an i-vector-based speaker recognition system. Using the LVT features alone, the system achieved a speaker recognition rate of 92.3% with 63 enrolled speakers. When the LVT features were fused with conventional MFCC features, the recognition rate was about equal to the recognition rate using MFCC features alone (> 98%). Y1 - 2024 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:898-opus4-70870 SN - 978-3-95908-325-6 SP - 108 EP - 115 PB - TUDpress CY - Dresden ER - TY - CHAP A1 - Draxler, Christoph A1 - Pömp, Julian ED - Baumann, Timo T1 - Octra Backend - Eine skalierbare Infrastruktur für Transkriptionsprojekte T2 - Elektronische Sprachsignalverarbeitung 2024, Tagungsband der 35. Konferenz, Regensburg, 6.-8. März 2024 N2 - Octra Backend ist eine portable web-basierte Infrastruktur für Transkriptionsprojekte, die lokal im Feld oder geschützten Bereichen, im begrenzten Intranet oder weltweit erreichbar im Internet eingesetzt werden kann. Entwicklungsziele waren die Gewährleistung möglichst hoher Sicherheitsanforderungen, eine gute Skalierbarkeit sowie eine einfache Installation auch ohne Administratorrechte. Octra Backend ist in Node.js implementiert und für MacOS, Windows und Linux verfügbar. Y1 - 2024 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:898-opus4-70867 SN - 978-3-95908-325-6 SP - 102 EP - 107 PB - TUDpress CY - Dresden ER - TY - GEN ED - Baumann, Timo ED - Siegert, Ingo T1 - Sprachassistenten: Anwendungen, Implikationen, Entwicklungen N2 - Der zweite ITG-Workshop „Sprachassistenten – Anwendungen, Implikationen, Entwicklungen“ fand am 5. März 2024 in Regensburg statt. Er bot eine organisatorische und inhaltliche Fortführung des ersten Workshops vor vier Jahren in Magdeburg 2020. Auch in diesem Jahr war er wieder der Konferenz Elektronische Sprachsignalverarbeitung angegliedert. Auf dem Workshop wurden vielfältige und interdisziplinäre Beiträge in eingeladenen Vorträgen und als eingereichte Poster präsentiert. Durch die gute Mischung von Beitragenden sowohl aus der Hochschullandschaft als auch aus der Industrie wurden die verschiedensten Aspekte anwendungsnah diskutiert. KW - Sprachassistenzsysteme KW - Digitaler Sprachassistent Y1 - 2024 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:898-opus4-71292 CY - Regensburg ER - TY - CHAP A1 - Mousavi, Neda A1 - Saeed Sarfjoo, Seyyed A1 - Grawunder, Sven ED - Baumann, Timo T1 - Unsupervised emotional pattern recognition using rhythmic and vocal features T2 - Elektronische Sprachsignalverarbeitung 2024, Tagungsband der 35. Konferenz, Regensburg, 6.-8. März 2024 N2 - In this study, we address the complex dynamics of emotional speech and comprehensively examine the integration of rhythmic and vocal features to recognize emotional patterns. Our exploration is conducted using two German emotional corpora: VMEmo and EmoDB. Employing a combination of supervised methods (here linear discriminant analysis, LDA) and unsupervised techniques (here k-means clustering), we aim to uncover nuanced patterns within the emotional speech in these corpora. The application of LDA highlights salient patterns across different feature sets and focuses on the classification of speakers and prosodic characteristics. In addition, k-means clustering uncovers latent structures that reveal subtle mapping between emotions and speech behavior. Our results suggest that it is possible to cluster data based on prosodic behaviors that are influenced by emotional changes. Although precise mapping to the actual clusters derived from emotional labels could not be fully achieved, the results nonetheless reveal a moderate level of success in this investigation. Y1 - 2024 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:898-opus4-71026 SN - 978-3-95908-325-6 SP - 233 EP - 240 PB - TUDpress CY - Dresden ER - TY - CHAP A1 - Ibrahim, Omnia A1 - Yuen, Ivan A1 - Xue, Wei A1 - Andreeva, Bistra A1 - Möbius, Bernd ED - Baumann, Timo T1 - Listener-Oriented Consequences of Predictability-Based Acoustic Adjustment T2 - Elektronische Sprachsignalverarbeitung 2024, Tagungsband der 35. Konferenz, Regensburg, 6.-8. März 2024 N2 - This paper investigated whether predictability-based adjustments in production have listener-oriented consequences in perception. By manipulating the acoustic features of a target syllable in different predictability contexts in German, we tested 40 listeners’ perceptual preference for the manipulation. Four source words underwent acoustic modifications on the target syllable. Our results revealed a general preference for the original (unmodified) version over the modified one. However, listeners generally favored the unmodified version more when the source word had a higher predictable context compared to a less predictable one. The results showed that predictability-based adjustments have perceptual consequences and that listeners have predictability-based expectations in perception. Y1 - 2024 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:898-opus4-70984 SN - 978-3-95908-325-6 SP - 196 EP - 202 PB - TUDpress CY - Dresden ER - TY - CHAP A1 - Ranzenberger, Thomas A1 - Bocklet, Tobias A1 - Freisinger, Steffen A1 - Georges, Munir A1 - Glocker, Kevin A1 - Herygers, Aaricia A1 - Riedhammer, Korbinian A1 - Schneider, Fabian A1 - Simic, Christopher A1 - Zakaria, Khabbab ED - Baumann, Timo T1 - Extending HAnS: Large Language Models For Question Answering, Summarization, And Topic Segmentation In An ML-based Learning Experience Platform T2 - Elektronische Sprachsignalverarbeitung 2024, Tagungsband der 35. Konferenz, Regensburg, 6.-8. März 2024 N2 - The use of chatbots based on large language models (LLMs) and their impact on society are influencing our learning experience platform Hochschul-Assistenz-System (HAnS). HAnS uses machine learning (ML) methods to support students and lecturers in the online learning and teaching processes [1]. This paper introduces LLM-based features available in HAnS which are using the transcript of our improved Automatic Speech Recognition (ASR) pipeline with an average transcription duration of 45 seconds and an average word error rate (WER) of 6.66% on over 8 hours of audio data of 7 lecture videos. A LLM-based chatbot could be used to answer questions on the lecture content as the ASR transcript is provided as context. The summarization and topic segmentation uses the LLM to improve our learning experience platform. We generate multiple choice questions using the LLM and the ASR transcript as context during playback in a period of 3 minutes and display them in the HAnS frontend. Y1 - 2024 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:898-opus4-71032 SN - 978-3-95908-325-6 SP - 219 EP - 224 PB - TUDpress CY - Dresden ER - TY - CHAP A1 - Kinoshita, Keisuke A1 - Delcroix, Marc A1 - Gannot, Sharon A1 - Habets, Emanuël A. P. A1 - Haeb-Umbach, Reinhold A1 - Kellermann, Walter A1 - Leutnant, Volker A1 - Maas, Roland A1 - Nakatani, Tomohiro A1 - Raj, Bhiksha A1 - Sehr, Armin A1 - Yoshioka, Takuya ED - Watanabe, Shinji ED - Delcroix, Marc ED - Metze, Florian ED - Hershey, John R. T1 - The REVERB Challenge: A Benchmark Task for Reverberation-Robust ASR Techniques T2 - New Era for Robust Speech Recognition N2 - The REVERB challenge is a benchmark task designed to evaluate reverberation-robust automatic speech recognition techniques under various conditions. A particular novelty of the REVERB challenge database is that it comprises both real reverberant speech recordings and simulated reverberant speech, both of which include tasks to evaluate techniques for 1-, 2-, and 8-microphone situations. In this chapter, we describe the problem of reverberation and characteristics of the REVERB challenge data, and finally briefly introduce some results and findings useful for reverberant speech processing in the current deep-neural-network era. Y1 - 2017 SN - 978-3-319-64679-4 U6 - https://doi.org/10.1007/978-3-319-64680-0_15 VL - 27 SP - 345 EP - 354 PB - Springer CY - Cham ER - TY - CHAP A1 - Kisser, Lea A1 - Busch, Matthias A1 - Siegert, Ingo ED - Baumann, Timo T1 - Review of Usage and Potentials of Conversational Interfaces at Universities and in Students Daily Lifes T2 - Elektronische Sprachsignalverarbeitung 2024, Tagungsband der 35. Konferenz, Regensburg, 6.-8. März 2024 N2 - The continuous advancement of digitization extends beyond educational institutions, giving rise to numerous innovations, particularly in the realm of study information [1]. One avenue for incorporating digital methodologies involves leveraging conversational agents (CAs) [2], serving as interactive interfaces bridging the gap between humans and computers. In the broader context, conversational agents are gaining prominence, offering several benefits to their users. The overarching goal is to comprehensively assist users through these intelligent systems. Consequently, exploring existing university chatbots becomes imperative to discern the areas where they excel. This research aims to scrutinize diverse chatbot systems, delving into their use cases and the challenges they encounter, employing a systematic review. Here it turns out that chatbots support universities the most in the fields of administration, e-learning and mental health. Furthermore, the study will investigate practical experiences on the potential applications and implementation of these systems in university settings, incorporating insights from an online survey and interviews, both made with experts. Here it comes to conclusion that preparation in relation to a chatbot implementation is the key factor to success. Otherwise, a failed system is nearly impossible to be saved, once users lost trust in the system. Therefore, carefully made preparations in the technical and organisational field are necessary to provide a helpful assistant. Y1 - 2024 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:898-opus4-70789 SN - 978-3-95908-325-6 SP - 38 EP - 45 PB - TUDpress CY - Dresden ER -