A remarkable phase of development: Speech-to-text technology

Swift development of artificial intelligence has being pushing revolutions in all walks of life, and the function of data is crucial. In the training process of AI models, high-quality datasets are like fuel, directly determines the performance and accuracy of the algorithm. With demand soaring for intelligence, various datasets have gradually become core resources for research and application.

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.

Nexdata Filipino Speech Data

522 Hours - Filipino Speech Data by Mobile Phone

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.

104 Hours - Filipino Conversational Speech Data by Mobile Phone

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.

With the in-depth application of artificial intelligence, the value of data has become prominent. Only with the support of massive high-quality data can AI technology breakthrough its bottlenecks and advance in a more intelligent and efficient direction. In the future, we need to continue to explore new ways of data collection and annotation to better cope with complex business requirements and achieve intelligent innovation.