res.set_content(ss.str(), "text/vtt");
} else if (params.response_format == vjson_format) {
/* try to match openai/whisper's Python format */
- std::string results = output_str(ctx, params, pcmf32s);
+ std::string results = output_str(ctx, params, pcmf32s);
+ // Get language probabilities
+ std::vector<float> lang_probs(whisper_lang_max_id() + 1, 0.0f);
+ const auto detected_lang_id = whisper_lang_auto_detect(ctx, 0, params.n_threads, lang_probs.data());
json jres = json{
{"task", params.translate ? "translate" : "transcribe"},
{"language", whisper_lang_str_full(whisper_full_lang_id(ctx))},
{"duration", float(pcmf32.size())/WHISPER_SAMPLE_RATE},
{"text", results},
- {"segments", json::array()}
+ {"segments", json::array()},
+ {"detected_language", whisper_lang_str_full(detected_lang_id)},
+ {"detected_language_probability", lang_probs[detected_lang_id]},
+ {"language_probabilities", json::object()}
};
+ // Add all language probabilities
+ for (int i = 0; i <= whisper_lang_max_id(); ++i) {
+ if (lang_probs[i] > 0.001f) { // Only include non-negligible probabilities
+ jres["language_probabilities"][whisper_lang_str(i)] = lang_probs[i];
+ }
+ }
const int n_segments = whisper_full_n_segments(ctx);
for (int i = 0; i < n_segments; ++i)
{