Fabio
c36510c21e
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80 lines
4 KiB
C++
80 lines
4 KiB
C++
// Optional real-library parity probe. No neural-model weights required.
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// Usage: probe <library> <espeak-ng-data> <sanotts|inflect|piper|concurrent>
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#include "engine/community_models/sanotts/frontend.h"
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#include "engine/community_models/inflect_v2/frontend.h"
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#include <future>
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#include <iostream>
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#include <stdexcept>
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#include <string>
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#include <vector>
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#include <unordered_map>
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static const std::vector<std::string> prompts = {
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"Hello, this is a native speech test.",
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"Good morning! How are you today?",
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"The price is $12.50, and the date is September 10, 2026.",
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"A short sentence; another clause: and a question?",
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"We should preserve pronunciation, punctuation, and token IDs."
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};
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template <class Frontend> void print(const Frontend & frontend) {
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for (const auto & text : prompts) {
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for (auto id : frontend.encode(text).token_ids) std::cout << id << ',';
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std::cout << '\n';
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}
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}
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int main(int argc, char ** argv) try {
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if (argc != 4) throw std::runtime_error("expected library, data directory and mode");
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using engine::models::sanotts::SanoTtsFrontend;
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using engine::models::inflect_v2::InflectV2Frontend;
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const std::string mode = argv[3];
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// '-' selects the compiled-in engine / executable-local data in static builds.
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if (std::string(argv[1]) == "-") argv[1][0] = '\0';
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if (std::string(argv[2]) == "-") argv[2][0] = '\0';
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if (mode == "sanotts") { SanoTtsFrontend f(argv[1], argv[2], 1000); print(f); }
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else if (mode == "inflect") { InflectV2Frontend f(argv[1], argv[2]); print(f); }
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else if (mode == "piper") {
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// Synthetic exhaustive IPA-range map tests the frontend independently
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// of model weights and per-voice token inventories.
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std::unordered_map<std::string, int32_t> ids;
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for (int cp = 0; cp < 1024; ++cp) {
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std::string utf8;
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if (cp < 128) utf8 += static_cast<char>(cp);
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else {
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utf8 += static_cast<char>(0xc0 | (cp >> 6));
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utf8 += static_cast<char>(0x80 | (cp & 63));
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}
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ids[utf8] = cp;
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}
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const std::vector<std::pair<std::string, std::string>> cases = {
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{"en-us", "Hello, how are you?"}, {"es", "Hola, buenos días."},
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{"fr", "Bonjour, comment allez-vous?"}, {"de", "Guten Morgen, wie geht es Ihnen?"},
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{"it", "Buongiorno, come stai?"}, {"pt-br", "Bom dia, como vai?"},
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{"pl", "Dzień dobry, jak się masz?"}, {"ru", "Доброе утро, как дела?"},
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{"hi", "नमस्ते आप कैसे हैं?"}, {"vi", "Xin chào, bạn khỏe không?"},
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{"id", "Selamat pagi, apa kabar?"}
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};
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for (const auto & item : cases) {
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engine::models::sanotts::SanoTtsPiperFrontend f(argv[1], argv[2], item.first, ids, 1000);
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std::cout << item.first << ':';
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for (auto id : f.encode(item.second).token_ids) std::cout << id << ',';
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std::cout << '\n';
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}
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}
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else if (mode == "concurrent") {
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SanoTtsFrontend sano(argv[1], argv[2], 1000);
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InflectV2Frontend inflect(argv[1], argv[2]);
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const auto run = [](const auto & frontend) {
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std::vector<std::vector<int32_t>> expected;
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for (const auto & text : prompts) expected.push_back(frontend.encode(text).token_ids);
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for (int repeat = 0; repeat < 20; ++repeat)
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for (size_t i = 0; i < prompts.size(); ++i)
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if (frontend.encode(prompts[i]).token_ids != expected[i])
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throw std::runtime_error("cross-model token mismatch");
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};
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auto a = std::async(std::launch::async, [&] { run(sano); });
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auto b = std::async(std::launch::async, [&] { run(inflect); });
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a.get(); b.get();
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std::cout << "200 cross-model real-library requests passed\n";
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} else throw std::runtime_error("unknown probe mode");
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return 0;
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} catch (const std::exception & e) { std::cerr << e.what() << '\n'; return 1; }
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