AI Voices for Voice Chatbots
Web chat is unusual because the visitor reads and listens at once. These voices suit an unhurried delivery, begin playing in about 200 milliseconds over WebSocket, and cover twelve languages from one integration.

VOICES FOR THIS USE CASE
Why chat is harder than narration
A narrator can be a second late and nobody notices. A chatbot cannot. Replies have to begin inside the pause a person expects in conversation, which means streaming rather than waiting for a complete file. Audio starts in about 200 milliseconds on the streaming endpoints, which is inside that window.
Handling a multilingual audience
Voices in the Indic family cover eleven Indic languages plus English, so one voice can answer a Hindi visitor and a Tamil visitor without re-casting. Switching the language parameter carries no latency penalty. The boundary is the European family, which those voices do not reach.
Voices that suit reading along
Web chat is unusual in that the visitor often reads the text while hearing it. That favours an unhurried delivery over an animated one, since the two channels compete for attention. 195 voices carry the conversational tag, which is the broadest group in the catalog and the right place to start casting.
Caching the predictable parts
Most chatbot output is repetitive. Greetings, confirmations and closings recur across nearly every session, and generating them repeatedly is wasted. Hashing the text and caching the audio removes most of the recurring cost, and it also makes those common replies instant rather than merely fast.
SPECIFICATION
Sample rate
44.1 kHz native, resampled to 8 kHz for telephony
Latency
~200 ms to first byte (p50, warm region)
Output formats
ulaw, alaw, PCM 16-bit, WAV, MP3
Streaming transports
WebSocket, HTTP chunked transfer
Speed range
0.5× – 2.0×, set per request
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AI Voices for Voice Chatbots
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