Google Cloud Text-to-Speech vs IBM Watson Text to Speech

Google Cloud Text-to-Speech is an API that converts text or SSML into audio data for applications. It offers more than 380 voices across more than 75 languages and variants, with REST or gRPC integration and output formats including MP3, LINEAR16, OGG_OPUS, MULAW, and ALAW. Gemini-TTS supports single- or multispeaker speech guided by natural-language prompts for style, accent, pace, tone, and emotional expression. Chirp 3 instant custom voice can create a personalized voice model from as little as 10 seconds of audio and is available in more than 30 locales. Streaming synthesis supports real-time conversations, while long-audio synthesis accepts up to 1 million bytes of input. Speech controls include pitch, speaking rate, and volume gain. Billing counts input characters, including spaces, newlines, and SSML tags except the mark tag, and billing must be enabled. Standard and WaveNet voices cost US$4 per 1 million characters, with 0 to 4 million characters free. Other voice models have different rates and free-use limits. New customers can receive $300 in Google Cloud credits.

IBM Watson Text to Speech is an API cloud service that converts written text into audio in multiple languages and voices, for applications or watsonx Assistant. Deep neural networks trained on human speech produce its neural voices. SSML controls can change pronunciation, volume, pitch, speed, and other attributes; unusual pronunciations can be specified with IPA or IBM SPR. Listed speaking styles include GoodNews, Apology, and Uncertainty, and voice transformation can adjust strength, pitch, breathiness, rate, and timbre. The service supports nine languages and accepts up to 5,000 input units. Export formats include A-law, Basic audio, FLAC, Linear 16-bit PCM, MP3, Mu-law, Ogg, WebM, and WAV. Deployment options include public, private, hybrid, multicloud, and on-premises infrastructure. Deploy Anywhere is billed by contacting IBM. Premium can include a custom branded neural voice modeled on a chosen speaker using as little as one hour of recordings.