#Japan #AI Data #Minato-ku #Qlean Dataset #Visual Bank

Visual Bank Unveils Qlean Dataset

Visual Bank Inc., based in Minato-ku, Tokyo, has made a significant addition to its AI training data solutions. Under its subsidiary, Amana Images Inc., the company has launched a new dataset titled "Japanese Two-Speaker Technology-Themed Speech Transcripts," which is part of the Qlean Dataset initiative. This dataset promises to be a valuable resource for researchers and developers working in the fields of natural language processing (NLP), automatic speech recognition (ASR), and conversational AI.

Overview of the Dataset

The newly released dataset comprises approximately 200 hours of natural, unscripted two-speaker dialogue focused on technology and IT topics. Each audio clip lasts between five to sixty minutes and is accompanied by corresponding transcripts. The conversations are varied, covering contemporary issues such as generative AI, relevant technological advancements, and everyday applications and ideas, providing a rich tapestry of discussion that mimics actual technical dialogue.

The dataset records dialogues among Japanese individuals, encompassing a diverse age range of 20s to 50s and depicting male and female speakers. The audio data is available in both wav and mp3 formats, along with text files in txt format. The dataset’s sampling rate stands at 44.1 kHz, ensuring high quality for research evaluations.

Use Cases for Research and Industry Applications

The Japanese Two-Speaker Technology Dialogue Dataset is designed to serve multiple purposes in both academic research and industrial applications. Here are some of its key use cases:

Research Applications

1. Analysis of Speaker Roles: It can be utilized to investigate how various dialogue roles—such as questions and explanations—are executed in technical discussions, analyzing the flow of conversation and the roles played by each speaker.
2. Evaluating ASR Models: Researchers can employ this dataset to evaluate the performance of speech recognition models on dialogues that include technical terminology and industry-specific language.
3. Dialogue Understanding: The dataset can help in verifying natural language processing models, especially in tracking topics and extracting key information from conversations related to cutting-edge technology.

Industrial Applications

1. Training Conversational AI: Organizations can use this dialogue data to train AI systems, enhancing their ability to understand and respond within technical contexts, which is crucial for developing chatbots and other conversational interfaces.
2. Transcription and Summarization Models: The wide-ranging discussions offer a basis for developing models that automatically transcribe and summarize technical dialogues, which is beneficial for creating educational materials and repurposing content for different platforms.
3. Validation for Technical Support Systems: The practical conversational data can be utilized to refine AI-driven support systems intended to aid users with various IT products and services, thereby improving their dialogical understanding.

About Qlean Dataset

The Qlean Dataset is a commercially available AI training data solution provided by Amana Images, aimed at facilitating safe and legal use for research and commercial operations. With partnerships through data partners, including Chiba Lotte Marines Co., Ltd. and Toyo Keizai Inc., Qlean Dataset continuously expands its offerings to align with industry demands and current trends.

Visual Bank envisions its Qlean Dataset initiative as a means to alleviate the overhead associated with data collection and preparation in AI development, establishing a legally compliant and risk-averse environment for innovation.

For more details, visit the Qlean Dataset website or the AI Data Recipe page.
Learn more about Visual Bank at their corporate site.