Human and Automatic Speech Recognition Performance on German Oral History Interviews

Two-Staged Acoustic Modeling Adaption for Robust Speech Recognition by the Example of German Oral History Interviews

In automatic speech recognition, often little training data is available for specific challenging tasks, but training of state-of-the-art automatic speech recognition systems requires large amounts of annotated speech. To address this issue, we propose a two-staged approach to acoustic modeling that combines noise and reverberation data augmentation with transfer learning to robustly address challenges such as difficult acoustic recording conditions, spontaneous speech, and speech of elderly people. We evaluate our approach using the example of German oral history interviews, where a relative …

Multi-Staged Cross-Lingual Acoustic Model Adaption for Robust Speech Recognition in Real-World Applications -- A Case Study on German Oral History Interviews

While recent automatic speech recognition systems achieve remarkable performance when large amounts of adequate, high quality annotated speech data is used for training, the same systems often only achieve an unsatisfactory result for tasks in domains that greatly deviate from the conditions represented by the training data. For many real-world applications, there is a lack of sufficient data that can be directly used for training robust speech recognition systems. To address this issue, we propose and investigate an approach that performs a robust acoustic model adaption to a target domain in…

A Study on the Ambiguity in Human Annotation of German Oral History Interviews for Perceived Emotion Recognition and Sentiment Analysis

For research in audiovisual interview archives often it is not only of interest what is said but also how. Sentiment analysis and emotion recognition can help capture, categorize and make these different facets searchable. In particular, for oral history archives, such indexing technologies can be of great interest. These technologies can help understand the role of emotions in historical remembering. However, humans often perceive sentiments and emotions ambiguously and subjectively. Moreover, oral history interviews have multi-layered levels of complex, sometimes contradictory, sometimes ver…

提示词层面上下文未检测到侧边级词错误率（WER）变化：对生产级口述历史语料库的预注册消融实验

No Detectable Change in Side-Level WER from Prompt-Level Context: A Preregistered Ablation on a Production Oral-History Corpus

该预注册实验在生产级口述历史转录工具上发现，提示词层面上下文未改变侧边级WER，仅短语有小幅改善，需结合序列对齐指标评估上下文机制。

InterView-C：一个同步的VR化身中介调查访谈多模态语料库

InterView-C: A Synchronized Multimodal Corpus of VR Avatar-Mediated Survey Interviews

InterView-C是一个德语多模态语料库，包含27次VR化身调查访谈，同步行为数据与人工转写，用于分析口语互动并解决ASR和迁移挑战。

Whisper 能理解瑞士德语吗？一项自动、定性与人工评估

Does Whisper understand Swiss German? An automatic, qualitative, and human evaluation

本文通过自动指标、定性分析和28人人工调查，在四个测试集上评估 Whisper 对瑞士德语的转写表现，证明其可作为输出标准德语的可行 ASR 系统。