Filipino Speech Data

In the field of machine learning and deep learning, datasets plays an irreplaceable role. No matter it is image data for convolutional neural networks or massive text data for natural language processing, the integrity and diversity of data directly determine the learning results of a model. With the advancement of technology, datasets that collected from specific scenarios have becomes the core strategy for improving model performance.

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.

The future intelligent system will increasingly rely on high-quality datasets to optimize decision-making and automated processes. In the era of data, companies and researchers need to continuously improve their ability of data collection and annotation to make sure the efficiency and accuracy of AI models. To gain an advantageous position in fiercely competitive market, we must laid a solid foundation in data.