Post by account_disabled on Jan 6, 2024 5:31:02 GMT
Aaudio in a way that allows it to be found quickly. The only way audio search would be possible on a global scale is through automated transcriptions. Manual transcriptions would require considerable time and effort for editors. KQEDs Olson notes that the level of accuracy needs to be high for audio transcriptions especially when it comes to indexing audio news. The advances made so far in speechtotext conversion do not currently meet those standards. Limitations of current speechtotext technology Google tested KQED and KUNGFU.AI applying the latest Speech to Text Tools to a collection of audio news. Limitations were discovered in as named entities. Named entities sometimes need context to be understood to be accurately identified something.
AI doesnt always have. Olson gives an example of KQED audio news that contains speech full of named entities that are contextual to the Bay Area region KQEDs Digital Marketing Service local news audio is rich with references to named entities related to topics people places and organizations that are contextual to the Bay Area region. Speakers use acronyms like CHP for the California Highway Patrol and the peninsula for the area stretching from San Francisco to San Jose. These are more difficult for artificial intelligence to identify. When the named entities are not understood the AI makes its best guess at what was said. However that is an unacceptable solution for web search because an incorrec.
Transcription can change the entire meaning of what was said. Whats Next Se continuar trabajando en la bsqueda de audio con planes para hacer que la tecnologa sea ampliamente accesible cuando se desarrolle. David Stoller socio lder de noticias y publicaciones en Google dice que la tecnologa se compartir abiertamente cuando se complete el trabajo en este proyecto. Uno de los pilares de Google New Initiative es incubar nuevos enfoques para problemas difciles. Una vez completada esta tecnologa y las mejores prcticas asociadas se compartirn abiertamente ampliando en gran medida el impacto anticipado. Los modelos.
AI doesnt always have. Olson gives an example of KQED audio news that contains speech full of named entities that are contextual to the Bay Area region KQEDs Digital Marketing Service local news audio is rich with references to named entities related to topics people places and organizations that are contextual to the Bay Area region. Speakers use acronyms like CHP for the California Highway Patrol and the peninsula for the area stretching from San Francisco to San Jose. These are more difficult for artificial intelligence to identify. When the named entities are not understood the AI makes its best guess at what was said. However that is an unacceptable solution for web search because an incorrec.
Transcription can change the entire meaning of what was said. Whats Next Se continuar trabajando en la bsqueda de audio con planes para hacer que la tecnologa sea ampliamente accesible cuando se desarrolle. David Stoller socio lder de noticias y publicaciones en Google dice que la tecnologa se compartir abiertamente cuando se complete el trabajo en este proyecto. Uno de los pilares de Google New Initiative es incubar nuevos enfoques para problemas difciles. Una vez completada esta tecnologa y las mejores prcticas asociadas se compartirn abiertamente ampliando en gran medida el impacto anticipado. Los modelos.