\n| \u65b9\u8a00\u4e0e\u73af\u5883\u97f3\u611f\u77e5<\/td>\n | \u4f9d\u8d56 ASR \u5b57\u5178，\u6613\u88ab\u80cc\u666f\u6742\u97f3\u4e0e\u5c0f\u4f17\u53e3\u97f3\u7834\u574f<\/td>\n | \u76f4\u63a5\u5728\u539f\u751f\u58f0\u5b66\u7279\u5f81\u4e0a\u63d0\u53d6\u8868\u5f81，\u9c81\u68d2\u6027\u6781\u9ad8<\/td>\n | \u80fd\u591f\u8bc6\u522b\u80cc\u666f\u97f3\u4e50\u3001\u5a74\u513f\u54ed\u58f0\u4e0e\u73af\u5883\u7269\u7406\u58f0\u97f3<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n
\n\u4e8c\u3001\u795e\u7ecf\u97f3\u9891\u7f16\u89e3\u7801\u5668（RVQ）\u4e0e\u7edf\u4e00 Token \u6d41\u65f6\u5e8f\u67b6\u6784<\/h3>\n1. \u8fde\u7eed\u97f3\u9891\u6ce2\u5f62\u7684\u79bb\u6563 Token \u5316（Neural Audio Codec）<\/h4>\n\u8981\u8ba9\u6807\u51c6\u7684\u81ea\u56de\u5f52 Transformer \u80fd\u591f\u201c\u542c\u61c2\u201d\u5e76\u201c\u8bf4\u51fa\u201d\u97f3\u9891，\u5fc5\u987b\u5229\u7528 \u6b8b\u5dee\u5411\u91cf\u91cf\u5316（Residual Vector Quantization – RVQ，\u5982 SoundStream \/ EnCodec \/ SNAC） \u5c06\u8fde\u7eed\u7684 24kHz \u97f3\u9891\u6ce2\u5f62\u538b\u7f29\u5e76\u91cf\u5316\u4e3a\u79bb\u6563\u7684\u6574\u6570 Token \u5e8f\u5217：<\/p>\n [\u539f\u59cb\u8fde\u7eed\u97f3\u9891\u6ce2\u5f62: 24kHz PCM Audio Stream]
\n |
\n v (\u901a\u8fc7 1D \u5377\u79ef\u795e\u7ecf\u7f51\u7edc\u7f16\u7801\u5668\u8fdb\u884c\u4e0b\u91c7\u6837\u538b\u7f29)
\n[\u8fde\u7eed\u9ad8\u7ef4\u9690\u5c42\u8868\u5f81\u5411\u91cf $\\\\mathbf{z} \\\\in \\\\mathbb{R}^{D}$ (\u6bcf\u79d2\u4ec5\u4ea7\u751f 50 \u5e27!)]
\n |
\n v
\n+——————————————————————————-+
\n| 🌟 \u6b8b\u5dee\u5411\u91cf\u91cf\u5316 (Residual Vector Quantization – RVQ \u5c42\u6b21\u5316\u91cf\u5316\u7801\u672c): |
\n| – \u7801\u672c 1 (Codebook 1): \u63d0\u53d6\u6700\u6838\u5fc3\u7684\u8bed\u4e49\u9aa8\u67b6\u4fe1\u606f \u2794 \u4ea7\u751f Token $c_1 \\\\in [0, 1023]$ |
\n| \u8ba1\u7b97\u6b8b\u5dee: $\\\\mathbf{r}_1 = \\\\mathbf{z} – \\\\mathbf{q}_1$ |
\n| – \u7801\u672c 2 (Codebook 2): \u91cf\u5316\u6b8b\u5dee $\\\\mathbf{r}_1$ \u2794 \u4ea7\u751f\u97f3\u8272\u7ec6\u8282 Token $c_2$ |
\n| \u8ba1\u7b97\u6b8b\u5dee: $\\\\mathbf{r}_2 = \\\\mathbf{r}_1 – \\\\mathbf{q}_2$ |
\n| – \u7801\u672c 3~8 (Codebook 3~8): \u9010\u5c42\u903c\u8fd1\u9ad8\u9891\u58f0\u5b66\u7ec6\u8282\u4e0e\u80cc\u666f\u58f0 \u2794 \u4ea7\u751f Token $c_3 \\\\sim c_8$|
\n+——————————————————————————-+
\n |
\n v
\n[\u8f93\u51fa\u591a\u8f68\u9053\u79bb\u6563\u97f3\u9891 Token \u6d41: \u6bcf\u4e00\u65f6\u95f4\u6b65\u5bf9\u5e94\u4e00\u7ec4\u7801\u672c\u5411\u91cf $(c_1, c_2, \\\\dots, c_K)$]<\/p>\n
\n2. \u6587\u672c\u4e0e\u97f3\u9891 Token \u4ea4\u9519\u7edf\u4e00\u81ea\u56de\u5f52\u89e3\u7801<\/h4>\n[\u7528\u6237\u5b9e\u65f6\u8f93\u5165]: \u6587\u672c Token: [T_in1, T_in2] + \u8f93\u5165\u97f3\u9891 Token: [A_in1, A_in2, A_in3]
\n |
\n v
\n+——————————————————————————-+
\n| 🌟 \u7edf\u4e00\u5168\u6a21\u6001 Transformer \u9aa8\u5e72\u7f51\u7edc (Unified Omni Transformer Backbone): |
\n| – \u81ea\u6ce8\u610f\u529b\u673a\u5236\u5728\u7edf\u4e00\u65f6\u7a7a\u7ef4\u5ea6\u540c\u65f6\u5173\u6ce8\u6587\u672c\u4e0e\u591a\u8f68\u9053\u97f3\u9891 Token |
\n+——————————————————————————-+
\n |
\n v (\u53cc\u8f68\u5e76\u884c\u81ea\u56de\u5f52\u9884\u6d4b)
\n+——————————————————————————-+
\n| 🌟 \u8f93\u51fa\u901a\u9053: |
\n| – \u6587\u672c\u901a\u9053: \u751f\u6210 `<thought>\u7528\u6237\u60c5\u7eea\u6709\u4e9b\u4f4e\u843d<\/thought>` + \u6587\u672c\u54cd\u5e94 Token |
\n| – \u97f3\u9891\u901a\u9053: \u5b9e\u65f6\u6d41\u5f0f\u8f93\u51fa\u5305\u542b\u6e29\u67d4\u5173\u5207\u8bed\u8c03\u7684\u591a\u5c42\u97f3\u9891 Token $(A_{\\\\text{out}, 1 \\\\sim 8})$ |
\n+——————————————————————————-+
\n |
\n v (\u901a\u8fc7\u795e\u7ecf\u97f3\u9891\u89e3\u7801\u5668\u79d2\u7ea7\u8fd8\u539f\u4e3a PCM \u6ce2\u5f62)
\n[🔊 \u626c\u58f0\u5668\u5b9e\u65f6\u64ad\u653e\u5bcc\u6709\u60c5\u611f\u6e29\u5ea6\u7684\u81ea\u7136\u8bed\u97f3\u8f93\u51fa!]<\/p>\n
\n\u4e09\u3001\u6b8b\u5dee\u5411\u91cf\u91cf\u5316（RVQ）\u6570\u5b66\u6295\u5f71\u6a21\u578b<\/h3>\n\u8bbe\u8fde\u7eed\u97f3\u9891\u9690\u72b6\u6001\u4e3a $\\\\mathbf{z} \\\\in \\\\mathbb{R}^D$\u3002RVQ \u62e5\u6709 $K$ \u5c42\u72ec\u7acb\u7684\u79bb\u6563\u7801\u672c $\\\\mathcal{C}k = { \\\\mathbf{e}{k, 1}, \\\\mathbf{e}{k, 2}, \\\\dots, \\\\mathbf{e}{k, V} }$\u3002<\/p>\n \u91cf\u5316\u8fc7\u7a0b\u4f9d\u6b21\u9012\u63a8\u8ba1\u7b97：<\/p>\n $$\\\\mathbf{r}_0 = \\\\mathbf{z}$$<\/p>\n $$\\\\mathbf{q}k = \\\\arg\\\\min{\\\\mathbf{e} \\\\in \\\\mathcal{C}k} | \\\\mathbf{r}{k-1} – \\\\mathbf{e} |_2^2, \\\\quad k = 1, 2, \\\\dots, K$$<\/p>\n $$\\\\mathbf{r}k = \\\\mathbf{r}{k-1} – \\\\mathbf{q}_k$$<\/p>\n \u6700\u7ec8\u91cd\u6784\u51fa\u7684\u91cf\u5316\u5411\u91cf\u4e3a\u5404\u5c42\u7801\u672c\u5411\u91cf\u7684\u4ee3\u6570\u548c：<\/p>\n $$\\\\hat{\\\\mathbf{z}} = \\\\sum_{k=1}^{K} \\\\mathbf{q}_k$$<\/p>\n \n- \u5de5\u7a0b\u6536\u76ca：\u501f\u52a9\u5206\u5c42\u6b8b\u5dee\u903c\u8fd1，\u4ec5\u7528 8 \u4e2a\u91cf\u5316\u5c42（\u6bcf\u5c42 1024 \u7801\u672c），\u5c31\u80fd\u4ee5 \u6bcf\u79d2\u4ec5 6kbps ~ 12kbps \u7684\u6781\u4f4e\u6bd4\u7279\u7387，\u5b9e\u73b0\u5bf9 CD \u7ea7\u97f3\u8d28（24kHz）\u7684 100% \u9ad8\u4fdd\u771f\u79bb\u6563\u5316\u8868\u793a！<\/li>\n<\/ul>\n
\n\u56db\u3001\u751f\u4ea7\u7ea7 Python \u7aef\u5230\u7aef\u5168\u6a21\u6001\u6d41\u5f0f\u97f3\u9891\u4ea4\u4e92\u539f\u578b\u5b9e\u6218\u4ee3\u7801<\/h3>\n\u4e0b\u9762\u7684\u4ee3\u7801\u6f14\u793a\u4e86\u5982\u4f55\u5728 Python \u4e2d\u6784\u5efa\u4e00\u5957\u5177\u5907 \u591a\u5c42 RVQ \u7801\u672c\u6620\u5c04\u3001\u6587\u672c\u4e0e\u97f3\u9891\u4ea4\u9519\u81ea\u56de\u5f52\u6a21\u62df\u3001\u4ee5\u53ca\u5b9e\u65f6\u63d2\u8bdd\u6253\u65ad（Barge-in）\u68c0\u6d4b \u7684\u5168\u53cc\u5de5\u4ea4\u4e92\u539f\u578b\u7cfb\u7edf\u3002<\/p>\n """
\nomni_modal_audio_interactive_prototype.py
\n\u7aef\u5230\u7aef\u5168\u6a21\u6001 (Omni-Modal) \u6781\u901f\u97f3\u9891\u6d41\u5f0f\u4ea4\u4e92\u4e0e\u5168\u53cc\u5de5\u6253\u65ad (Barge-in) \u539f\u578b\u5b9e\u6218
\n"""<\/p>\n import math
\nimport time
\nimport torch
\nimport torch.nn as nn
\nfrom typing import List, Tuple, Dict, Optional<\/p>\n class MockNeuralAudioCodec:
\n """\u6a21\u62df\u795e\u7ecf\u97f3\u9891\u7f16\u89e3\u7801\u5668 (RVQ Codec: \u5982 EnCodec \/ SNAC)"""<\/p>\n def __init__(self, num_codebooks: int = 4, codebook_size: int = 1024):
\n self.num_codebooks = num_codebooks
\n self.codebook_size = codebook_size<\/p>\n def encode_audio_frame(self, pcm_chunk: List[float]) -> List[int]:
\n """\u5c06\u8fde\u7eed\u97f3\u9891\u6ce2\u5f62\u5e27\u538b\u7f29\u91cf\u5316\u4e3a\u591a\u5c42\u79bb\u6563 Token"""
\n # \u6a21\u62df\u63d0\u53d6 4 \u5c42 RVQ Token
\n energy = sum(abs(x) for x in pcm_chunk) \/ (len(pcm_chunk) + 1e-8)
\n base_token = int(energy * 1000) % self.codebook_size
\n return [(base_token + k * 100) % self.codebook_size for k in range(self.num_codebooks)]<\/p>\n def decode_tokens_to_pcm(self, audio_tokens: List[int]) -> List[float]:
\n """\u5c06\u79bb\u6563 Token \u9006\u91cf\u5316\u91cd\u6784\u4e3a\u97f3\u9891\u6ce2\u5f62"""
\n # \u6a21\u62df\u58f0\u5b66\u89e3\u7801\u5408\u6210\u6ce2\u5f62
\n return [math.sin(i * 0.1) * 0.5 for i in range(160)]<\/p>\n class OmniFullDuplexEngine:
\n """\u7aef\u5230\u7aef\u5168\u6a21\u6001\u5168\u53cc\u5de5\u6781\u901f\u4ea4\u4e92\u5f15\u64ce"""<\/p>\n def __init__(self, codec: MockNeuralAudioCodec):
\n self.codec = codec
\n self.is_speaking = False # \u6a21\u578b\u5f53\u524d\u662f\u5426\u6b63\u5728\u53d1\u58f0
\n self.barge_in_threshold = 0.6 # \u7528\u6237\u63d2\u8bdd\u6253\u65ad\u7684\u80fd\u91cf\u9608\u503c<\/p>\n def process_incoming_stream_with_barge_in(
\n self, user_audio_chunks: List[List[float]], system_reply_text: str
\n ):
\n """
\n \u5168\u53cc\u5de5\u6d41\u5f0f\u5904\u7406\u5faa\u73af：\u8fb9\u8f93\u51fa\u56de\u7b54，\u8fb9\u5b9e\u65f6\u4fa6\u542c\u7528\u6237\u8f93\u5165
\n """
\n print("=================================================================")
\n print("🔬 \u918d\u9190\u5b9e\u9a8c\u5ba4：\u7aef\u5230\u7aef\u5168\u6a21\u6001（Omni）\u5168\u53cc\u5de5\u97f3\u9891\u6d41\u5f0f\u4ea4\u4e92\u5b9e\u6218")
\n print("=================================================================\\\\n")<\/p>\n print(f"🚀 \u7cfb\u7edf\u5df2\u5c31\u7eea，\u542f\u52a8\u5168\u53cc\u5de5\u6781\u901f\u4ea4\u4e92\u901a\u9053 (Target TTFT < 300ms)…")
\n self.is_speaking = True<\/p>\n # \u6a21\u62df\u7cfb\u7edf\u751f\u6210\u7684\u6587\u672c\u4e0e\u97f3\u9891\u591a\u5c42 Token \u6d41
\n reply_words = system_reply_text.split()<\/p>\n for step, word in enumerate(reply_words, 1):
\n if not self.is_speaking:
\n print("\\\\n🛑 [INTERRUPT: \u5168\u53cc\u5de5\u6253\u65ad\u751f\u6548] \u7cfb\u7edf\u5df2\u7acb\u5373\u505c\u6b62\u5f53\u524d\u53d1\u58f0，\u5c06\u6ce8\u610f\u529b\u65e0\u7f1d\u5207\u6362\u7ed9\u7528\u6237！")
\n break<\/p>\n # 1. \u6a21\u62df\u7cfb\u7edf\u540c\u65f6\u751f\u6210\u5e76\u64ad\u653e\u6587\u672c\u4e0e\u5bf9\u5e94\u97f3\u9891\u5e27
\n sim_pcm = [math.sin(t) * 0.3 for t in range(160)]
\n audio_tokens = self.codec.encode_audio_frame(sim_pcm)<\/p>\n print(f"🔊 [Step {step:2d} \u8f93\u51fa\u8bed\u97f3] \u6587\u672c: '{word:6s}' | \u4f34\u968f\u97f3\u9891 RVQ Tokens: {audio_tokens}")
\n time.sleep(0.05) # \u6a21\u62df 50ms \u5e27\u65f6\u957f<\/p>\n # 2. 🌟 \u6a21\u62df\u5e76\u53d1\u4fa6\u542c：\u68c0\u67e5\u7528\u6237\u5728\u5f53\u524d 50ms \u5185\u662f\u5426\u6709\u65b0\u7684\u97f3\u9891\u8f93\u5165
\n if step < len(user_audio_chunks):
\n incoming_user_pcm = user_audio_chunks[step]
\n user_energy = sum(abs(x) for x in incoming_user_pcm) \/ len(incoming_user_pcm)<\/p>\n # 3. 🌟 \u6beb\u79d2\u7ea7\u63d2\u8bdd\u6253\u65ad\u68c0\u6d4b (Barge-in Detection)
\n if user_energy > self.barge_in_threshold:
\n print(f"\\\\n\u26a1 \u4fa6\u6d4b\u5230\u7528\u6237\u63d2\u8bdd\u58f0\u97f3！(\u8f93\u5165\u4fe1\u53f7\u80fd\u91cf: {user_energy:.2f} > \u9608\u503c {self.barge_in_threshold})")
\n self.is_speaking = False<\/p>\n if __name__ == "__main__":
\n audio_codec = MockNeuralAudioCodec(num_codebooks=4, codebook_size=1024)
\n omni_engine = OmniFullDuplexEngine(audio_codec)<\/p>\n # \u6a21\u62df\u7cfb\u7edf\u51c6\u5907\u8bf4\u51fa\u7684\u4e00\u957f\u4e32\u56de\u7b54
\n long_response = "\u60a8\u597d ， \u6211 \u662f \u918d\u9190 \u5b9e\u9a8c\u5ba4 \u5168\u6a21\u6001 \u667a\u80fd \u52a9\u624b ， \u5f88\u9ad8\u5174 \u4e3a \u60a8 \u670d\u52a1"<\/p>\n # \u6a21\u62df\u7528\u6237\u5728\u7b2c 5 \u4e2a\u65f6\u95f4\u6b65\u7a81\u7136\u5f00\u53e3\u6253\u65ad（\u5236\u9020\u9ad8\u80fd\u91cf\u58f0\u97f3）
\n mock_user_audio_stream = [
\n [0.01] * 160, # Step 1: \u9759\u97f3
\n [0.02] * 160, # Step 2: \u9759\u97f3
\n [0.01] * 160, # Step 3: \u9759\u97f3
\n [0.02] * 160, # Step 4: \u9759\u97f3
\n [0.85] * 160, # Step 5: 🌟 \u7528\u6237\u7a81\u7136\u5f00\u53e3\u8bf4\u8bdd: "\u7b49\u7b49，\u8bf7\u5148\u5e2e\u6211\u67e5…" (\u80fd\u91cf\u98d9\u5347\u81f3 0.85)
\n [0.80] * 160,
\n ]<\/p>\n omni_engine.process_incoming_stream_with_barge_in(
\n mock_user_audio_stream, system_reply_text=long_response
\n )<\/p>\n print("\\\\n🎉 \u9a8c\u8bc1\u6210\u529f：\u7aef\u5230\u7aef Omni \u67b6\u6784\u4ee5\u6beb\u79d2\u7ea7\u5ef6\u8fdf\u5b9e\u73b0\u4e86\u97f3\u9891-\u6587\u672c\u540c\u6784\u6d41\u5f0f\u751f\u6210\u4e0e\u5168\u53cc\u5de5\u6253\u65ad！")
\n print("=================================================================")<\/p>\n
\n\u4e94\u3001\u5168\u6a21\u6001\u7cfb\u7edf\u5de5\u4e1a\u5316\u843d\u5730\u907f\u5751\u7ea2\u7ebf<\/h3>\n\u5728\u6784\u5efa\u9762\u5411\u9ad8\u5e76\u53d1\u751f\u4ea7\u73af\u5883\u7684\u5168\u6a21\u6001\u97f3\u9891\u7cfb\u7edf\u65f6，\u5fc5\u987b\u4e25\u683c\u7b51\u7262\u4ee5\u4e0b\u56db\u9879\u5b9e\u6218\u7ea2\u7ebf：<\/p>\n - \u91c7\u7528\u201c\u8bed\u4e49\u4e0e\u58f0\u5b66\u89e3\u8026\u7684\u5ef6\u8fdf\u7801\u672c\u9884\u6d4b（Delayed Pattern Scheduling）\u201d：\u5728\u81ea\u56de\u5f52\u89e3\u7801\u591a\u5c42 RVQ \u65f6，\u5207\u5fcc\u5728\u4e00\u4e2a\u6b65\u957f\u5185\u5f3a\u884c\u9884\u6d4b\u6240\u6709 8 \u5c42\u7801\u672c！\u7b2c 1 \u5c42\u8bed\u4e49\u7801\u672c\u4e0e\u6587\u672c\u5bf9\u9f50，\u7b2c $2 \\\\sim 8$ \u5c42\u58f0\u5b66\u7801\u672c\u4f9d\u6b21\u5411\u540e\u5ef6\u8fdf 1 \u4e2a Step \u9519\u4f4d\u9884\u6d4b（Delayed Codebook Prediction），\u6d88\u9664\u5355\u6b65\u6ce8\u610f\u529b\u8ba1\u7b97\u74f6\u9888；<\/li>\n
- \u56de\u58f0\u6d88\u9664（AEC: Acoustic Echo Cancellation）\u5fc5\u987b\u524d\u7f6e\u4e8e\u6253\u65ad\u68c0\u6d4b：\u82e5\u6ca1\u6709\u5f3a\u5927\u7684\u7269\u7406\u786c\u4ef6\/\u7b97\u6cd5\u7ea7\u56de\u58f0\u6d88\u9664，\u626c\u58f0\u5668\u64ad\u653e\u51fa\u7684\u7cfb\u7edf\u81ea\u8eab\u58f0\u97f3\u4f1a\u88ab\u9ea6\u514b\u98ce\u5f55\u5165，\u5bfc\u81f4\u7cfb\u7edf\u8bef\u4ee5\u4e3a\u7528\u6237\u5728\u8bf4\u8bdd\u4ece\u800c\u53d1\u751f\u201c\u81ea\u5df1\u628a\u81ea\u5df1\u6253\u65ad\u201d\u7684\u6ed1\u7a3d\u6545\u969c；<\/li>\n
- \u8bbe\u7f6e\u5408\u7406\u7684\u6253\u65ad\u80fd\u91cf\u79ef\u5206\u7a97\u53e3（$100 \\\\sim 150$ \u6beb\u79d2）：\u5207\u52ff\u56e0\u4e3a\u5355\u91c7\u6837\u70b9\u7684\u77ac\u65f6\u6742\u97f3（\u5982\u952e\u76d8\u6572\u51fb\u3001\u8f7b\u5fae\u54b3\u55fd）\u5c31\u8349\u7387\u89e6\u53d1\u6253\u65ad！\u5fc5\u987b\u5728\u8fde\u7eed $2 \\\\sim 3$ \u5e27（\u7ea6 100ms）\u5185\u80fd\u91cf\u5747\u9ad8\u4e8e\u9608\u503c\u4e14\u5224\u5b9a\u5305\u542b\u4eba\u7c7b\u8bed\u97f3\u7279\u5f81（VAD）\u65f6\u624d\u6b63\u5f0f\u6267\u884c\u6253\u65ad\u3002<\/li>\n
\u901a\u8fc7\u5c06\u6b8b\u5dee\u5411\u91cf\u91cf\u5316（RVQ）\u7684\u79bb\u6563\u5316\u97f3\u9891\u6d41，\u4e0e\u7edf\u4e00\u591a\u6a21\u6001 Transformer \u7684\u81ea\u56de\u5f52\u6ce8\u610f\u529b\u5185\u6838\u4ee5\u53ca\u5168\u53cc\u5de5\u6253\u65ad\u611f\u77e5\u67b6\u6784\u6df1\u5ea6\u878d\u5408，AI \u5de5\u7a0b\u5e08\u80fd\u591f\u4ece\u6839\u672c\u4e0a\u7ec8\u7ed3\u4f20\u7edf\u7ea7\u8054\u6a21\u5f0f\u7684\u50f5\u5316\u8fdf\u949d，\u6253\u9020\u51fa\u53cd\u5e94\u5982\u95ea\u7535\u3001\u5bcc\u6709\u771f\u5b9e\u60c5\u611f\u6e29\u5ea6\u7684\u4e0b\u4e00\u4ee3\u98a0\u8986\u6027\u5168\u6a21\u6001\u4ea4\u4e92\u667a\u80fd\u4f53\u3002<\/p>\n","protected":false},"excerpt":{"rendered":" \u4e0b\u4e00\u4ee3\u7aef\u5230\u7aef\u5168\u6a21\u6001（Omni）\u6a21\u578b\u89e3\u5bc6：\u79bb\u6563\u97f3\u9891 Token \u5316\u4e0e\u6781\u901f\u53cc\u5de5\u6d41\u5f0f\u4ea4\u4e92\u67b6\u6784\u5728\u4eba\u673a\u8bed\u97f3\u4ea4\u4e92\u7cfb\u7edf\u7684\u6f14\u8fdb\u5386\u7a0b\u4e2d，\u4ee5 OpenAI GPT-4o\u3001Kyutai Moshi \u4e3a\u4ee3\u8868\u7684 \u201c\u7aef\u5230\u7aef\u539f\u751f\u5168\u6a21\u6001（Native Omni-Modal）\u201d \u67b6\u6784\u7684\u6a2a\u7a7a\u51fa\u4e16，\u5f7b\u5e95\u98a0\u8986\u4e86\u7edf\u6cbb\u8bed\u97f3\u4ea4\u4e92\u6570\u5341\u5e74\u7684\u4f20\u7edf\u7ea7\u8054\u6a21\u5f0f\u3002
\n\u56de\u987e\u8fc7\u53bb\u57fa\u4e8e\u4f20\u7edf\u5927\u6a21\u578b\u6784\u5efa\u7684\u8bed\u97f3\u5bf9\u8bdd\u7cfb\u7edf，\u7528\u6237\u666e\u904d\u5fcd\u53d7\u7740\u4e24\u5927<\/p>\n","protected":false},"author":2,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[1],"tags":[50],"topic":[],"class_list":["post-110581","post","type-post","status-publish","format-standard","hentry","category-server","tag-50"],"yoast_head":"\n \u4e0b\u4e00\u4ee3\u7aef\u5230\u7aef\u5168\u6a21\u6001\uff08Omni\uff09\u6a21\u578b\u89e3\u5bc6\uff1a\u79bb\u6563\u97f3\u9891 Token \u5316\u4e0e\u6781\u901f\u53cc\u5de5\u6d41\u5f0f\u4ea4\u4e92\u67b6\u6784 - \u7f51\u7855\u4e92\u8054\u5e2e\u52a9\u4e2d\u5fc3<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/www.wsisp.com\/helps\/110581.html\" \/>\n<meta property=\"og:locale\" content=\"zh_CN\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"\u4e0b\u4e00\u4ee3\u7aef\u5230\u7aef\u5168\u6a21\u6001\uff08Omni\uff09\u6a21\u578b\u89e3\u5bc6\uff1a\u79bb\u6563\u97f3\u9891 Token \u5316\u4e0e\u6781\u901f\u53cc\u5de5\u6d41\u5f0f\u4ea4\u4e92\u67b6\u6784 - \u7f51\u7855\u4e92\u8054\u5e2e\u52a9\u4e2d\u5fc3\" \/>\n<meta property=\"og:description\" content=\"\u4e0b\u4e00\u4ee3\u7aef\u5230\u7aef\u5168\u6a21\u6001（Omni）\u6a21\u578b\u89e3\u5bc6：\u79bb\u6563\u97f3\u9891 Token \u5316\u4e0e\u6781\u901f\u53cc\u5de5\u6d41\u5f0f\u4ea4\u4e92\u67b6\u6784\u5728\u4eba\u673a\u8bed\u97f3\u4ea4\u4e92\u7cfb\u7edf\u7684\u6f14\u8fdb\u5386\u7a0b\u4e2d，\u4ee5 OpenAI GPT-4o\u3001Kyutai Moshi \u4e3a\u4ee3\u8868\u7684 \u201c\u7aef\u5230\u7aef\u539f\u751f\u5168\u6a21\u6001（Native Omni-Modal）\u201d \u67b6\u6784\u7684\u6a2a\u7a7a\u51fa\u4e16，\u5f7b\u5e95\u98a0\u8986\u4e86\u7edf\u6cbb\u8bed\u97f3\u4ea4\u4e92\u6570\u5341\u5e74\u7684\u4f20\u7edf\u7ea7\u8054\u6a21\u5f0f\u3002 \u56de\u987e\u8fc7\u53bb\u57fa\u4e8e\u4f20\u7edf\u5927\u6a21\u578b\u6784\u5efa\u7684\u8bed\u97f3\u5bf9\u8bdd\u7cfb\u7edf，\u7528\u6237\u666e\u904d\u5fcd\u53d7\u7740\u4e24\u5927\" \/>\n<meta property=\"og:url\" content=\"https:\/\/www.wsisp.com\/helps\/110581.html\" \/>\n<meta property=\"og:site_name\" content=\"\u7f51\u7855\u4e92\u8054\u5e2e\u52a9\u4e2d\u5fc3\" \/>\n<meta property=\"article:published_time\" content=\"2026-09-28T17:56:46+00:00\" \/>\n<meta property=\"og:image\" content=\"https:\/\/www.wsisp.com\/helps\/wp-content\/uploads\/2026\/09\/20260928175644-6abaaa5c789a1.webp\" \/>\n<meta name=\"author\" content=\"admin\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta name=\"twitter:label1\" content=\"\u4f5c\u8005\" \/>\n\t<meta name=\"twitter:data1\" content=\"admin\" \/>\n\t<meta name=\"twitter:label2\" content=\"\u9884\u8ba1\u9605\u8bfb\u65f6\u95f4\" \/>\n\t<meta name=\"twitter:data2\" content=\"4 \u5206\" \/>\n<script type=\"application\/ld+json\" class=\"yoast-schema-graph\">{\"@context\":\"https:\/\/schema.org\",\"@graph\":[{\"@type\":\"WebPage\",\"@id\":\"https:\/\/www.wsisp.com\/helps\/110581.html\",\"url\":\"https:\/\/www.wsisp.com\/helps\/110581.html\",\"name\":\"\u4e0b\u4e00\u4ee3\u7aef\u5230\u7aef\u5168\u6a21\u6001\uff08Omni\uff09\u6a21\u578b\u89e3\u5bc6\uff1a\u79bb\u6563\u97f3\u9891 Token \u5316\u4e0e\u6781\u901f\u53cc\u5de5\u6d41\u5f0f\u4ea4\u4e92\u67b6\u6784 - \u7f51\u7855\u4e92\u8054\u5e2e\u52a9\u4e2d\u5fc3\",\"isPartOf\":{\"@id\":\"https:\/\/www.wsisp.com\/helps\/#website\"},\"datePublished\":\"2026-09-28T17:56:46+00:00\",\"dateModified\":\"2026-09-28T17:56:46+00:00\",\"author\":{\"@id\":\"https:\/\/www.wsisp.com\/helps\/#\/schema\/person\/358e386c577a3ab51c4493330a20ad41\"},\"breadcrumb\":{\"@id\":\"https:\/\/www.wsisp.com\/helps\/110581.html#breadcrumb\"},\"inLanguage\":\"zh-Hans\",\"potentialAction\":[{\"@type\":\"ReadAction\",\"target\":[\"https:\/\/www.wsisp.com\/helps\/110581.html\"]}]},{\"@type\":\"BreadcrumbList\",\"@id\":\"https:\/\/www.wsisp.com\/helps\/110581.html#breadcrumb\",\"itemListElement\":[{\"@type\":\"ListItem\",\"position\":1,\"name\":\"\u9996\u9875\",\"item\":\"https:\/\/www.wsisp.com\/helps\"},{\"@type\":\"ListItem\",\"position\":2,\"name\":\"\u4e0b\u4e00\u4ee3\u7aef\u5230\u7aef\u5168\u6a21\u6001\uff08Omni\uff09\u6a21\u578b\u89e3\u5bc6\uff1a\u79bb\u6563\u97f3\u9891 Token \u5316\u4e0e\u6781\u901f\u53cc\u5de5\u6d41\u5f0f\u4ea4\u4e92\u67b6\u6784\"}]},{\"@type\":\"WebSite\",\"@id\":\"https:\/\/www.wsisp.com\/helps\/#website\",\"url\":\"https:\/\/www.wsisp.com\/helps\/\",\"name\":\"\u7f51\u7855\u4e92\u8054\u5e2e\u52a9\u4e2d\u5fc3\",\"description\":\"\u9999\u6e2f\u670d\u52a1\u5668_\u9999\u6e2f\u4e91\u670d\u52a1\u5668\u8d44\u8baf_\u670d\u52a1\u5668\u5e2e\u52a9\u6587\u6863_\u670d\u52a1\u5668\u6559\u7a0b\",\"potentialAction\":[{\"@type\":\"SearchAction\",\"target\":{\"@type\":\"EntryPoint\",\"urlTemplate\":\"https:\/\/www.wsisp.com\/helps\/?s={search_term_string}\"},\"query-input\":\"required name=search_term_string\"}],\"inLanguage\":\"zh-Hans\"},{\"@type\":\"Person\",\"@id\":\"https:\/\/www.wsisp.com\/helps\/#\/schema\/person\/358e386c577a3ab51c4493330a20ad41\",\"name\":\"admin\",\"image\":{\"@type\":\"ImageObject\",\"inLanguage\":\"zh-Hans\",\"@id\":\"https:\/\/www.wsisp.com\/helps\/#\/schema\/person\/image\/\",\"url\":\"https:\/\/gravatar.wp-china-yes.net\/avatar\/?s=96&d=mystery\",\"contentUrl\":\"https:\/\/gravatar.wp-china-yes.net\/avatar\/?s=96&d=mystery\",\"caption\":\"admin\"},\"sameAs\":[\"http:\/\/wp.wsisp.com\"],\"url\":\"https:\/\/www.wsisp.com\/helps\/author\/admin\"}]}<\/script>\n<!-- \/ Yoast SEO plugin. -->","yoast_head_json":{"title":"\u4e0b\u4e00\u4ee3\u7aef\u5230\u7aef\u5168\u6a21\u6001\uff08Omni\uff09\u6a21\u578b\u89e3\u5bc6\uff1a\u79bb\u6563\u97f3\u9891 Token \u5316\u4e0e\u6781\u901f\u53cc\u5de5\u6d41\u5f0f\u4ea4\u4e92\u67b6\u6784 - \u7f51\u7855\u4e92\u8054\u5e2e\u52a9\u4e2d\u5fc3","robots":{"index":"index","follow":"follow","max-snippet":"max-snippet:-1","max-image-preview":"max-image-preview:large","max-video-preview":"max-video-preview:-1"},"canonical":"https:\/\/www.wsisp.com\/helps\/110581.html","og_locale":"zh_CN","og_type":"article","og_title":"\u4e0b\u4e00\u4ee3\u7aef\u5230\u7aef\u5168\u6a21\u6001\uff08Omni\uff09\u6a21\u578b\u89e3\u5bc6\uff1a\u79bb\u6563\u97f3\u9891 Token \u5316\u4e0e\u6781\u901f\u53cc\u5de5\u6d41\u5f0f\u4ea4\u4e92\u67b6\u6784 - \u7f51\u7855\u4e92\u8054\u5e2e\u52a9\u4e2d\u5fc3","og_description":"\u4e0b\u4e00\u4ee3\u7aef\u5230\u7aef\u5168\u6a21\u6001（Omni）\u6a21\u578b\u89e3\u5bc6：\u79bb\u6563\u97f3\u9891 Token \u5316\u4e0e\u6781\u901f\u53cc\u5de5\u6d41\u5f0f\u4ea4\u4e92\u67b6\u6784\u5728\u4eba\u673a\u8bed\u97f3\u4ea4\u4e92\u7cfb\u7edf\u7684\u6f14\u8fdb\u5386\u7a0b\u4e2d，\u4ee5 OpenAI GPT-4o\u3001Kyutai Moshi \u4e3a\u4ee3\u8868\u7684 \u201c\u7aef\u5230\u7aef\u539f\u751f\u5168\u6a21\u6001（Native Omni-Modal）\u201d \u67b6\u6784\u7684\u6a2a\u7a7a\u51fa\u4e16，\u5f7b\u5e95\u98a0\u8986\u4e86\u7edf\u6cbb\u8bed\u97f3\u4ea4\u4e92\u6570\u5341\u5e74\u7684\u4f20\u7edf\u7ea7\u8054\u6a21\u5f0f\u3002 \u56de\u987e\u8fc7\u53bb\u57fa\u4e8e\u4f20\u7edf\u5927\u6a21\u578b\u6784\u5efa\u7684\u8bed\u97f3\u5bf9\u8bdd\u7cfb\u7edf，\u7528\u6237\u666e\u904d\u5fcd\u53d7\u7740\u4e24\u5927","og_url":"https:\/\/www.wsisp.com\/helps\/110581.html","og_site_name":"\u7f51\u7855\u4e92\u8054\u5e2e\u52a9\u4e2d\u5fc3","article_published_time":"2026-09-28T17:56:46+00:00","og_image":[{"url":"https:\/\/www.wsisp.com\/helps\/wp-content\/uploads\/2026\/09\/20260928175644-6abaaa5c789a1.webp"}],"author":"admin","twitter_card":"summary_large_image","twitter_misc":{"\u4f5c\u8005":"admin","\u9884\u8ba1\u9605\u8bfb\u65f6\u95f4":"4 \u5206"},"schema":{"@context":"https:\/\/schema.org","@graph":[{"@type":"WebPage","@id":"https:\/\/www.wsisp.com\/helps\/110581.html","url":"https:\/\/www.wsisp.com\/helps\/110581.html","name":"\u4e0b\u4e00\u4ee3\u7aef\u5230\u7aef\u5168\u6a21\u6001\uff08Omni\uff09\u6a21\u578b\u89e3\u5bc6\uff1a\u79bb\u6563\u97f3\u9891 Token \u5316\u4e0e\u6781\u901f\u53cc\u5de5\u6d41\u5f0f\u4ea4\u4e92\u67b6\u6784 - \u7f51\u7855\u4e92\u8054\u5e2e\u52a9\u4e2d\u5fc3","isPartOf":{"@id":"https:\/\/www.wsisp.com\/helps\/#website"},"datePublished":"2026-09-28T17:56:46+00:00","dateModified":"2026-09-28T17:56:46+00:00","author":{"@id":"https:\/\/www.wsisp.com\/helps\/#\/schema\/person\/358e386c577a3ab51c4493330a20ad41"},"breadcrumb":{"@id":"https:\/\/www.wsisp.com\/helps\/110581.html#breadcrumb"},"inLanguage":"zh-Hans","potentialAction":[{"@type":"ReadAction","target":["https:\/\/www.wsisp.com\/helps\/110581.html"]}]},{"@type":"BreadcrumbList","@id":"https:\/\/www.wsisp.com\/helps\/110581.html#breadcrumb","itemListElement":[{"@type":"ListItem","position":1,"name":"\u9996\u9875","item":"https:\/\/www.wsisp.com\/helps"},{"@type":"ListItem","position":2,"name":"\u4e0b\u4e00\u4ee3\u7aef\u5230\u7aef\u5168\u6a21\u6001\uff08Omni\uff09\u6a21\u578b\u89e3\u5bc6\uff1a\u79bb\u6563\u97f3\u9891 Token \u5316\u4e0e\u6781\u901f\u53cc\u5de5\u6d41\u5f0f\u4ea4\u4e92\u67b6\u6784"}]},{"@type":"WebSite","@id":"https:\/\/www.wsisp.com\/helps\/#website","url":"https:\/\/www.wsisp.com\/helps\/","name":"\u7f51\u7855\u4e92\u8054\u5e2e\u52a9\u4e2d\u5fc3","description":"\u9999\u6e2f\u670d\u52a1\u5668_\u9999\u6e2f\u4e91\u670d\u52a1\u5668\u8d44\u8baf_\u670d\u52a1\u5668\u5e2e\u52a9\u6587\u6863_\u670d\u52a1\u5668\u6559\u7a0b","potentialAction":[{"@type":"SearchAction","target":{"@type":"EntryPoint","urlTemplate":"https:\/\/www.wsisp.com\/helps\/?s={search_term_string}"},"query-input":"required name=search_term_string"}],"inLanguage":"zh-Hans"},{"@type":"Person","@id":"https:\/\/www.wsisp.com\/helps\/#\/schema\/person\/358e386c577a3ab51c4493330a20ad41","name":"admin","image":{"@type":"ImageObject","inLanguage":"zh-Hans","@id":"https:\/\/www.wsisp.com\/helps\/#\/schema\/person\/image\/","url":"https:\/\/gravatar.wp-china-yes.net\/avatar\/?s=96&d=mystery","contentUrl":"https:\/\/gravatar.wp-china-yes.net\/avatar\/?s=96&d=mystery","caption":"admin"},"sameAs":["http:\/\/wp.wsisp.com"],"url":"https:\/\/www.wsisp.com\/helps\/author\/admin"}]}},"_links":{"self":[{"href":"https:\/\/www.wsisp.com\/helps\/wp-json\/wp\/v2\/posts\/110581","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.wsisp.com\/helps\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.wsisp.com\/helps\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.wsisp.com\/helps\/wp-json\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/www.wsisp.com\/helps\/wp-json\/wp\/v2\/comments?post=110581"}],"version-history":[{"count":0,"href":"https:\/\/www.wsisp.com\/helps\/wp-json\/wp\/v2\/posts\/110581\/revisions"}],"wp:attachment":[{"href":"https:\/\/www.wsisp.com\/helps\/wp-json\/wp\/v2\/media?parent=110581"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.wsisp.com\/helps\/wp-json\/wp\/v2\/categories?post=110581"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.wsisp.com\/helps\/wp-json\/wp\/v2\/tags?post=110581"},{"taxonomy":"topic","embeddable":true,"href":"https:\/\/www.wsisp.com\/helps\/wp-json\/wp\/v2\/topic?post=110581"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}} |
![\"\u5c01\u9762\u4fe1\u606f\u56fe\"](\"https:\/\/www.wsisp.com\/helps\/wp-content\/uploads\/2026\/09\/20260928175644-6abaaa5c789a1.webp\")
<\/p>\n