芬兰议会ASR集体:分析,基准和统计数据
Anja Virkkunen1, Aku Rouhe1, Nhan Phan1
1Department of Information and Communications Engineering, Aalto University, Espoo, Finland.
概括
芬兰议会ASR库提供了广泛的语音转录数据,用于改进自动语音识别 (ASR) 系统. 分析显示HMM-TDNN性能高原,而wav2vec 2.0模型从更多的数据中受益.
科学领域:
- 语音处理 语音处理
- 计算语言学 计算语言学
- 机器学习 机器学习
背景情况:
- 公共可用的议会录音是培训和评估自动语音识别 (ASR) 系统的宝贵资源.
- 现有的数据集往往缺乏足够的规模或详细的元数据来进行强大的ASR开发.
研究的目的:
- 介绍和分析芬兰议会ASR集体,这是最大的公开可用的芬兰语语音数据集.
- 建立基准并评估本集体上的各种ASR系统架构,考虑纵向分布变化.
主要方法:
- 开发了基于Kaldi的数据准备管道和ASR配方,用于隐藏的马尔科夫模型 (HMM),HMM深度神经网络 (HMM-DNN) 和基于注意力的编码解码器 (AED).
- 使用时间延迟神经网络 (TDNN) 和先进的 wav2vec 2.0 预训练声学模型进行评估的系统.
- 对官方和外部测试集进行比较分析,包括HMM-DNN和AED的相同数据设置.
主要成果:
- 芬兰议会ASR集体包含来自449名发言人的3000多小时的演讲,以及人口统计元数据.
- HMM-TDNN ASR系统在官方测试集上达到性能高原,尽管体积大小.
- 较大的 wav2vec 2.0 模型显示了额外数据的好处,在某些场景中表现优于 HMM-DNN.
- 在匹配的数据设置中,HMM-DNN系统的性能始终优于AED系统.
结论:
- 芬兰议会ASR库是促进芬兰ASR研究的重要资源.
- 研究了ASR性能趋势,并确定了需要改进的领域,特别是在大型预训练模型中.
- 初步分析表明,在不同发言人群 (性别,年龄,教育) 中,ASR准确度存在潜在偏差.
相关概念视频
Archival Research
16.0K
Some researchers gain access to large amounts of data without interacting with a single research participant. Instead, they use existing records to answer various research questions. This type of research approach is known as archival research. Archival research relies on looking at past records or data sets to look for interesting patterns or relationships. For example, a researcher might access the academic records of all individuals who enrolled in college within the past ten years and...
16.0K
Statistical Analysis System (SAS)
238
SAS, short for Statistical Analysis System, is a powerful data analysis, management, and visualization tool. Developed by the SAS Institute in the early 1970s, SAS has evolved into a comprehensive software suite used across various industries for statistical analysis, business intelligence, and predictive modeling.
Applications: SAS finds applications in numerous fields, including healthcare for clinical trial analysis, finance for risk assessment, marketing for customer data analysis, and...
Applications: SAS finds applications in numerous fields, including healthcare for clinical trial analysis, finance for risk assessment, marketing for customer data analysis, and...
238
Statistical Analysis: Overview
6.7K
When we take repeated measurements on the same or replicated samples, we will observe inconsistencies in the magnitude. These inconsistencies are called errors. To categorize and characterize these results and their errors, the researcher can use statistical analysis to determine the quality of the measurements and/or suitability of the methods.
One of the most commonly used statistical quantifiers is the mean, which is the ratio between the sum of the numerical values of all results and the...
One of the most commonly used statistical quantifiers is the mean, which is the ratio between the sum of the numerical values of all results and the...
6.7K
Statistical Methods to Analyze Parametric Data: ANOVA
444
Analysis of Variance, or ANOVA, is a powerful statistical technique used to analyze parametric data, primarily in research and experimental studies. It's designed to compare the means of two or more groups, assisting researchers in identifying any significant differences between these group means. There are two main types of ANOVA based on the complexity of the analysis: one-way and two-way.
One-way ANOVA is applied when a single independent variable or factor is scrutinized. It compares...
One-way ANOVA is applied when a single independent variable or factor is scrutinized. It compares...
444
One-Way ANOVA
8.0K
One-way ANOVA analyzes more than three samples categorized by one factor. For example, it can compare the average mileage of sports bikes. Here, the data is categorized by one factor - the company. However, one-way ANOVA cannot be used to simultaneously compare the sample mean of three or more samples categorized by two factors. An example of two factors would be sports bikes from different companies driven in different terrains, such as a desert or snowy landscape. Here, two-way ANOVA is used...
8.0K
Two-Way ANOVA
2.7K
The two-way ANOVA is an extension of the one-way ANOVA. It is a statistical test performed on three or more samples categorized by two factors - a row factor and a column factor. Ronald Fischer mentioned it in 1925 in his book 'Statistical Methods for Researchers.'
The two-way ANOVA analysis initially begins by stating the null hypothesis that there is an interaction effect between the two factors of a dataset. This effect can be visualized using line segments formed by joining the...
The two-way ANOVA analysis initially begins by stating the null hypothesis that there is an interaction effect between the two factors of a dataset. This effect can be visualized using line segments formed by joining the...
2.7K


