results: 对Whisper模型进行finetuning后，对儿童语音识别表现出显著改善，而使用自然语言生成模型wav2vec2进行finetuning则超过了Whisper模型的表现。Abstract
Automatic Speech Recognition (ASR) systems often struggle with transcribing child speech due to the lack of large child speech datasets required to accurately train child-friendly ASR models. However, there are huge amounts of annotated adult speech datasets which were used to create multilingual ASR models, such as Whisper. Our work aims to explore whether such models can be adapted to child speech to improve ASR for children. In addition, we compare Whisper child-adaptations with finetuned self-supervised models, such as wav2vec2. We demonstrate that finetuning Whisper on child speech yields significant improvements in ASR performance on child speech, compared to non finetuned Whisper models. Additionally, utilizing self-supervised Wav2vec2 models that have been finetuned on child speech outperforms Whisper finetuning.
摘要
自动语音识别（ASR）系统经常遇到儿童语音识别问题，原因在于缺乏儿童语音数据集，以训练适合儿童的 ASR 模型。然而，有大量已注解的成人语音数据集，用于创建多语言 ASR 模型，如呐喊（Whisper）。我们的工作旨在探讨是否可以将这些模型适应儿童语音，以提高 ASR 性能。此外，我们还比较了呐喊儿童化的模型与自动学习的 wav2vec2 模型，并证明了后者在儿童语音识别中表现更优。
Performance Comparison Between VoLTE and non-VoLTE Voice Calls During Mobility in Commercial Deployment: A Drive Test-Based Analysis
methods: 该研究使用了 XCAL 驱动测试工具收集实时网络参数数据，并对 VoLTE 和非 VoLTE 语音呼电中的实时网络特性进行分析。
results: 研究发现，使用 VoLTE 技术可以提高 call setup delay 的速度和 UE 电池寿命，并且在 VoLTE 和非 VoLTE 语音呼电中比较研究了 DRX 机制。这些结果可以帮助优化移动通信网络的质量服务 (QoS)。Abstract
The optimization of network performance is vital for the delivery of services using standard cellular technologies for mobile communications. Call setup delay and User Equipment (UE) battery savings significantly influence network performance. Improving these factors is vital for ensuring optimal service delivery. In comparison to traditional circuit-switched voice calls, VoLTE (Voice over LTE) technology offers faster call setup durations and better battery-saving performance. To validate these claims, a drive test was carried out using the XCAL drive test tool to collect real-time network parameter details in VoLTE and non-VoLTE voice calls. The findings highlight the analysis of real-time network characteristics, such as the call setup delay calculation, battery-saving performance, and DRX mechanism. The study contributes to the understanding of network optimization strategies and provides insights for enhancing the quality of service (QoS) in mobile communication networks. Examining VoLTE and non-VoLTE operations, this research highlights the substantial energy savings obtained by VoLTE. Specifically, VoLTE saves approximately 60.76% of energy before the Service Request and approximately 38.97% of energy after the Service Request. Moreover, VoLTE to VoLTE calls have a 72.6% faster call setup delay than non-VoLTE-based LTE to LTE calls, because of fewer signaling messages required. Furthermore, as compared to non-VoLTE to non-VoLTE calls, VoLTE to non-VoLTE calls offer an 18.6% faster call setup delay. These results showcase the performance advantages of VoLTE and reinforce its potential for offering better services in wireless communication networks.
摘要
网络性能优化对于通过标准无线通信技术提供服务是非常重要。启动延迟和用户设备（UE）电池寿命具有重要影响力。提高这些因素对于确保优质服务的提供是非常重要。与传统的循环连接语音电话相比，VoLTE（音声在LTE）技术提供了更快的启动延迟和更好的电池寿命性能。为了证明这些声明，我们使用了XCAL驱动测试工具来收集实时网络参数详细信息在VoLTE和非VoLTE语音电话中。研究结果显示了实时网络特性的分析，包括启动延迟计算、电池寿命性能和DRX机制。这项研究对网络优化策略的理解和服务质量（QoS）的提高做出了贡献。对VoLTE和非VoLTE操作进行比较，这项研究显示了VoLTE可以获得约60.76%的电源储存和约38.97%的电源储存。此外，VoLTE到VoLTE电话的启动延迟比非VoLTE基于LTE到LTE电话的启动延迟更快，这是因为VoLTE需要 fewer signaling messages。此外，VoLTE到非VoLTE电话的启动延迟比非VoLTE到非VoLTE电话的启动延迟更快，这是因为VoLTE需要更少的信号处理。这些结果显示了VoLTE的性能优势，并证明它在无线通信网络中可以提供更好的服务。