wuyang6
62 lines
2.6 KiB
JavaScript
62 lines
2.6 KiB
JavaScript
export function queueSteps(chunkMs, computeMs, count = 8) {
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if (
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!Number.isFinite(chunkMs) ||
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!Number.isFinite(computeMs) ||
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chunkMs <= 0 ||
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computeMs <= 0
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) {
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throw new RangeError("Time values must be finite and positive.");
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}
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let previousEnd = 0;
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return Array.from({ length: count }, (_, index) => {
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const arrival = (index + 1) * chunkMs;
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const start = Math.max(arrival, previousEnd);
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const end = start + computeMs;
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previousEnd = end;
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return { index: index + 1, arrival, start, end, wait: start - arrival };
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});
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}
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export const architectures = {
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cascade: {
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nodes: [
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["用户语音", "声音输入", "input"],
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["ASR", "识别成文本"],
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["文本 LLM", "生成回答"],
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["TTS", "合成声音"],
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["系统语音", "播放输出", "output"],
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],
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detail:
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"<p><strong>两个独立的文本接口。</strong>ASR 把用户语音交给文本模型，TTS 再把回答读出。模块可以独立替换。仅传文字时，输入声学信息会在接口处被压缩。</p><p>持续双工需要在这些模块之间保持新输入、话轮状态、取消与播放进度的一致。</p>",
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},
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two: {
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nodes: [
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["用户语音", "声音输入", "input"],
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["语音理解 LLM", "直接读取音频特征"],
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["回答文本", "内容接口"],
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["TTS", "合成声音"],
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["系统语音", "播放输出", "output"],
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],
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detail:
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"<p><strong>输入端直接理解声音。</strong>模型接收音频特征并生成回答文字，之后由独立 TTS 合成。输入端可以保留语气等线索，输出端仍通过文本接口组织。</p><p>本页以 Ultravox 核心加外接 TTS 作为这一工作定义的例子。</p>",
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},
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native: {
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nodes: [
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["用户语音", "声音输入", "input"],
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["语音表示", "编码或特征"],
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["联合交互模型", "声音与内容建模"],
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["语音解码", "还原波形"],
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["系统语音", "播放输出", "output"],
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],
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detail:
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"<p><strong>语音直接参与内容与声学生成。</strong>编码器、音频 token、文字辅助流和波形解码器可以共同存在，具体组织依模型而异。</p><p>持续听说依赖输入更新方式、因果训练与实时服务。原生语音接口与全双工行为分别核验。</p>",
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},
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};
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export const benchmarks = [
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{ name: "级联管线", first: 8.78, answer: 10.12 },
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{ name: "Ultravox 0.7", first: 3.88, answer: 8.4 },
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{ name: "GPT-Realtime 1.5", first: 6.36, answer: 6.89 },
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{ name: "Gemini Live 3.1", first: 3.95, answer: 4.25 },
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];
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