Please fill in your name
Mobile phone format error
Please enter the telephone
Please enter your company name
Please enter your company email
Please enter the data requirement
Successful submission! Thank you for your support.
Format error, Please fill in again
The data requirement cannot be less than 5 words and cannot be pure numbers
Speech recognition technology has made significant advancements in recent years, revolutionizing various aspects of our lives. One particular area where this technology has had a profound impact is in the Filipino community.
Filipino, as the national language of the Philippines, is spoken by millions of people both in the country and across the globe. However, the complexity of the Filipino language, with its rich vocabulary and diverse accents, has posed challenges for speech recognition systems in accurately transcribing spoken words.
Fortunately, researchers and developers have recognized the importance of addressing this issue and have been working tirelessly to improve Filipino speech recognition technology. Through the use of advanced machine learning algorithms and extensive data sets, these efforts have resulted in remarkable progress.
Datatang Filipino Speech Data
522 Hours - Filipino Speech Data by Mobile Phone，the data were recorded by Filipino speakers with authentic Filipino accents.The text is manually proofread with high accuracy. Match mainstream Android, Apple system phones.
The 104 Hours - Filipino Conversational Speech Data by Mobile Phone collected by phone involved 140 native speakers, developed with proper balance of gender ratio, Speakers would choose a few familiar topics out of the given list and start conversations to ensure dialogues' fluency and naturalness. The recording devices are various mobile phones. The audio format is 16kHz, 16bit, uncompressed WAV, and all the speech data was recorded in quiet indoor environments. All the speech audio was manually transcribed with text content, the start and end time of each effective sentence, and speaker identification.
The use of off-the-shelf datasets in developing advanced AI solutions for enterprises has sparked a heated debate. Particularly for organizations lacking in-house expertise, such as data scientists, engineers, and annotation teams, off-the-shelf datasets offer an ideal solution.
In recent years, the field of artificial intelligence (AI) has witnessed remarkable advancements, with generative AI and multi-modal data playing a pivotal role in shaping the future of technology. This article explores the synergistic relationship between these two concepts and their potential to revolutionize various industries.