*- Speech Pipelines * Copilots can generate ready-to-use code for speech-to-text and text-to-speech using APIs like OpenAI Whisper, Azure AI Speech, and Google Cloud Speech-to-Text. For example, a developer can ask for a transcription setup in Python and get working code within seconds — useful for customer support, meeting notes, or language learning apps. - Source: dev.to / 10 days ago

Google Cloud Speech-to-Text API is a powerful tool for transforming audio into actionable insights. Its accuracy, scalability, and customization options make it a valuable asset for a wide range of applications. By understanding its features, capabilities, and best practices, you can unlock the full potential of speech recognition and build intelligent applications that understand and respond to the world around... - Source: dev.to / 3 months ago

Google, YouTube’s parent company, has invested heavily in speech recognition research. Their Cloud Speech-to-Text API is one of the most advanced in the world, and its technology forms the backbone of YouTube’s captioning system. The API uses neural networks to process audio, identify phonemes (the smallest units of sound), and assemble them into words and sentences. - Source: dev.to / 5 months ago

Cloud-based speech recognition solutions, such as Google Cloud Speech-to-Text and Microsoft Azure Speech, have gained popularity due to their accessibility, power, and scalability. Developers gain access to ready-to-use APIs with high-quality speech recognition models. However, behind this convenience are several important technical aspects that need to be considered when choosing a cloud solution. - Source: dev.to / 10 months ago

APIs from Major Providers. Leading tech companies offer SDKs that support on-premise speech recognition, such as Lingvanex On-premise Speech Recognition, Google’s Speech-to-Text and Microsoft’s Speech SDK. Although these may offer more functionalities, it’s essential to evaluate their suitability for local processing. **Custom Solutions. - Source: dev.to / 12 months ago

Picovoice processes on the device and you can fine-tune the models https://picovoice.ai/platform/cat/. - Source: Hacker News / over 2 years ago

Oh, Azure's speech recognition API beats it handily on English language. Both in accuracy and speed. Another is Deepgram. Even this obscure vendor seems to be able to handle the samples I tried: https://picovoice.ai/platform/cat/. - Source: Hacker News / over 2 years ago

Day 23 is the day to show how to run an ASR (Automatic Speech Recognition) with Picovoice Leopard Speech-to-Text and AWS Lambda. - Source: dev.to / over 2 years ago

Historically, there’s been several roadblocks to local transcription. Not anymore with Picovoice Leopard Speech-to-Text SDK for cross-platform .NET. - Source: dev.to / over 2 years ago

After getting a transcription request, the server starts an instance of Leopard and keeps reading the shipped bytes until the EOF. Then, the bytes are stored as a temporary file and passed to Leopard. Finally, the transcription is sent back to the client side along with a status code. - Source: dev.to / over 2 years ago