Brief — wiretap

{
  "payload": {
    "transcript": "In this discussion, Derek, Harsh, and a third speaker analyze the evolution of startup trends in Silicon Valley by comparing recent batch statistics with those from four years ago. They highlight the overwhelming dominance of AI startups, which now make up nearly 70% of the current batch, a significant increase from just 8% in 2020. They reflect on early AI pioneers like Replicate and note how the AI landscape has transformed over the years. Additionally, the conversation touches on the resurgence of consumer-focused startups, with some founders pivoting back to consumer ideas instead of enterprise solutions, sparking a debate about whether this shift is positive or potentially a sign of complacency.",
    "segments": [],
    "language": null
  },
  "meta": {
    "time": "2026-07-13T03:24:16.705Z",
    "provider": "tinycloud",
    "model": "cloudglue",
    "mode": "speech",
    "case": "case:wiretap"
  },
  "media": {
    "ref": "showcase/_media/wiretap/interview-tape.wav"
  }
}

{
  "payload": {
    "op": "separate",
    "input": "showcase/_media/wiretap/interview-tape.wav",
    "model": "pyannote/speaker-diarization-community-1",
    "speakers": 4,
    "count": 4,
    "overlap": [
      {
        "at": [
          37.05,
          37.68
        ],
        "speakers": [
          "SPEAKER_00",
          "SPEAKER_03"
        ]
      },
      {
        "at": [
          37.86,
          38.22
        ],
        "speakers": [
          "SPEAKER_02",
          "SPEAKER_03"
        ]
      },
      {
        "at": [
          69.2,
          69.25
        ],
        "speakers": [
          "SPEAKER_00",
          "SPEAKER_02"
        ]
      },
      {
        "at": [
          69.25,
          70.15
        ],
        "speakers": [
          "SPEAKER_00",
          "SPEAKER_03"
        ]
      }
    ],
    "outputs": [
      {
        "kind": "track",
        "ref": "case:wiretap/.overcast/media/separate/interview-tape_SPEAKER_00.wav",
        "speaker": "SPEAKER_00",
        "speech_seconds": 5.86,
        "segments": [
          {
            "at": [
              37.05,
              37.68
            ]
          },
          {
            "at": [
              66.35,
              70.15
            ]
          },
          {
            "at": [
              104.62,
              106.06
            ]
          }
        ],
        "overlap": [
          {
            "at": [
              37.05,
              37.68
            ],
            "speakers": [
              "SPEAKER_00",
              "SPEAKER_03"
            ]
          },
          {
            "at": [
              69.2,
              69.25
            ],
            "speakers": [
              "SPEAKER_00",
              "SPEAKER_02"
            ]
          },
          {
            "at": [
              69.25,
              70.15
            ],
            "speakers": [
              "SPEAKER_00",
              "SPEAKER_03"
            ]
          }
        ]
      },
      {
        "kind": "track",
        "ref": "case:wiretap/.overcast/media/separate/interview-tape_SPEAKER_01.wav",
        "speaker": "SPEAKER_01",
        "speech_seconds": 17.96,
        "segments": [
          {
            "at": [
              0.03,
              4.25
            ]
          },
          {
            "at": [
              4.89,
              9.18
            ]
          },
          {
            "at": [
              38.24,
              39.96
            ]
          },
          {
            "at": [
              40.43,
              48.16
            ]
          }
        ],
        "overlap": []
      },
      {
        "kind": "track",
        "ref": "case:wiretap/.overcast/media/separate/interview-tape_SPEAKER_02.wav",
        "speaker": "SPEAKER_02",
        "speech_seconds": 30.29,
        "segments": [
          {
            "at": [
              9.48,
              14
            ]
          },
          {
            "at": [
              21.7,
              29.11
            ]
          },
          {
            "at": [
              37.86,
              38.22
            ]
          },
          {
            "at": [
              39.96,
              40.28
            ]
          },
          {
            "at": [
              48.55,
              66.18
            ]
          },
          {
            "at": [
              69.2,
              69.25
            ]
          }
        ],
        "overlap": [
          {
            "at": [
              37.86,
              38.22
            ],
            "speakers": [
              "SPEAKER_02",
              "SPEAKER_03"
            ]
          },
          {
            "at": [
              69.2,
              69.25
            ],
            "speakers": [
              "SPEAKER_00",
              "SPEAKER_02"
            ]
          }
        ]
      },
      {
        "kind": "track",
        "ref": "case:wiretap/.overcast/media/separate/interview-tape_SPEAKER_03.wav",
        "speaker": "SPEAKER_03",
        "speech_seconds": 63.97,
        "segments": [
          {
            "at": [
              14.12,
              21.7
            ]
          },
          {
            "at": [
              29.11,
              38.24
            ]
          },
          {
            "at": [
              69.25,
              97.86
            ]
          },
          {
            "at": [
              98.34,
              103.68
            ]
          },
          {
            "at": [
              106.65,
              119.98
            ]
          }
        ],
        "overlap": [
          {
            "at": [
              37.05,
              37.68
            ],
            "speakers": [
              "SPEAKER_00",
              "SPEAKER_03"
            ]
          },
          {
            "at": [
              37.86,
              38.22
            ],
            "speakers": [
              "SPEAKER_02",
              "SPEAKER_03"
            ]
          },
          {
            "at": [
              69.25,
              70.15
            ],
            "speakers": [
              "SPEAKER_00",
              "SPEAKER_03"
            ]
          }
        ]
      }
    ]
  },
  "meta": {
    "time": "2026-07-13T03:25:08.535Z",
    "provider": "local:pyannote",
    "model": "pyannote/speaker-diarization-community-1",
    "case": "case:wiretap"
  },
  "media": {
    "ref": "showcase/_media/wiretap/interview-tape.wav"
  }
}

{
  "payload": {
    "summary": "separated SPEAKER_00 from interview-tape.wav (5.9s speech) — The video features a conversation reflecting on the early days of artificial intelligence, highlighting how the technology was originally referred to as machine learning rather than AI. The speakers discuss their amazement at the developments in the field and contemplate the implications of AI, ques…",
    "op": "separate",
    "source_record": "rec_285619d83592acbd",
    "source_media": "showcase/_media/wiretap/interview-tape.wav",
    "kind": "track",
    "speaker": "SPEAKER_00",
    "speech_seconds": 5.86,
    "segments": [
      {
        "at": [
          37.05,
          37.68
        ]
      },
      {
        "at": [
          66.35,
          70.15
        ]
      },
      {
        "at": [
          104.62,
          106.06
        ]
      }
    ],
    "overlap": [
      {
        "at": [
          37.05,
          37.68
        ],
        "speakers": [
          "SPEAKER_00",
          "SPEAKER_03"
        ]
      },
      {
        "at": [
          69.2,
          69.25
        ],
        "speakers": [
          "SPEAKER_00",
          "SPEAKER_02"
        ]
      },
      {
        "at": [
          69.25,
          70.15
        ],
        "speakers": [
          "SPEAKER_00",
          "SPEAKER_03"
        ]
      }
    ],
    "transcript": "The video features a conversation reflecting on the early days of artificial intelligence, highlighting how the technology was originally referred to as machine learning rather than AI. The speakers discuss their amazement at the developments in the field and contemplate the implications of AI, questioning whether its impact will be positive or negative.",
    "listen_provider": "tinycloud"
  },
  "meta": {
    "time": "2026-07-13T03:25:08.535Z",
    "provider": "local:pyannote",
    "case": "case:wiretap"
  },
  "media": {
    "ref": "case:wiretap/.overcast/media/separate/interview-tape_SPEAKER_00.wav"
  }
}

{
  "payload": {
    "summary": "separated SPEAKER_01 from interview-tape.wav (18.0s speech) — The video features a discussion where Speaker 1 compares statistics of startup batches from four years ago to the current batch, highlighting a significant increase in the number of companies involved—from 8% in winter 2020 to about 170 companies in the latest batch. The conversation briefly mention…",
    "op": "separate",
    "source_record": "rec_285619d83592acbd",
    "source_media": "showcase/_media/wiretap/interview-tape.wav",
    "kind": "track",
    "speaker": "SPEAKER_01",
    "speech_seconds": 17.96,
    "segments": [
      {
        "at": [
          0.03,
          4.25
        ]
      },
      {
        "at": [
          4.89,
          9.18
        ]
      },
      {
        "at": [
          38.24,
          39.96
        ]
      },
      {
        "at": [
          40.43,
          48.16
        ]
      }
    ],
    "overlap": [],
    "transcript": "The video features a discussion where Speaker 1 compares statistics of startup batches from four years ago to the current batch, highlighting a significant increase in the number of companies involved—from 8% in winter 2020 to about 170 companies in the latest batch. The conversation briefly mentions notable companies such as Replicate from the earlier batch.",
    "listen_provider": "tinycloud"
  },
  "meta": {
    "time": "2026-07-13T03:25:08.535Z",
    "provider": "local:pyannote",
    "case": "case:wiretap"
  },
  "media": {
    "ref": "case:wiretap/.overcast/media/separate/interview-tape_SPEAKER_01.wav"
  }
}

{
  "payload": {
    "summary": "separated SPEAKER_02 from interview-tape.wav (30.3s speech) — The video discusses the current major trends in Silicon Valley, focusing primarily on the rapid rise of artificial intelligence (AI) as the dominant megatrend over the past year. The speaker highlights how early AI-focused founders, such as those at Replicate, were ahead of the curve and benefited f…",
    "op": "separate",
    "source_record": "rec_285619d83592acbd",
    "source_media": "showcase/_media/wiretap/interview-tape.wav",
    "kind": "track",
    "speaker": "SPEAKER_02",
    "speech_seconds": 30.29,
    "segments": [
      {
        "at": [
          9.48,
          14
        ]
      },
      {
        "at": [
          21.7,
          29.11
        ]
      },
      {
        "at": [
          37.86,
          38.22
        ]
      },
      {
        "at": [
          39.96,
          40.28
        ]
      },
      {
        "at": [
          48.55,
          66.18
        ]
      },
      {
        "at": [
          69.2,
          69.25
        ]
      }
    ],
    "overlap": [
      {
        "at": [
          37.86,
          38.22
        ],
        "speakers": [
          "SPEAKER_02",
          "SPEAKER_03"
        ]
      },
      {
        "at": [
          69.2,
          69.25
        ],
        "speakers": [
          "SPEAKER_00",
          "SPEAKER_02"
        ]
      }
    ],
    "transcript": "The video discusses the current major trends in Silicon Valley, focusing primarily on the rapid rise of artificial intelligence (AI) as the dominant megatrend over the past year. The speaker highlights how early AI-focused founders, such as those at Replicate, were ahead of the curve and benefited from the growing interest in AI. However, the initial years were challenging due to a limited customer base and fewer people working directly in AI, as the company initially built tools for AI developers.",
    "listen_provider": "tinycloud"
  },
  "meta": {
    "time": "2026-07-13T03:25:08.535Z",
    "provider": "local:pyannote",
    "case": "case:wiretap"
  },
  "media": {
    "ref": "case:wiretap/.overcast/media/separate/interview-tape_SPEAKER_02.wav"
  }
}

{
  "payload": {
    "summary": "separated SPEAKER_03 from interview-tape.wav (64.0s speech) — The video features a discussion about notable trends observed in the Winter 2024 startup batch, highlighting that nearly 70% of the ideas involve AI and machine learning. A key shift identified is the resurgence of consumer-focused startups, with founders increasingly pivoting towards consumer ideas…",
    "op": "separate",
    "source_record": "rec_285619d83592acbd",
    "source_media": "showcase/_media/wiretap/interview-tape.wav",
    "kind": "track",
    "speaker": "SPEAKER_03",
    "speech_seconds": 63.97,
    "segments": [
      {
        "at": [
          14.12,
          21.7
        ]
      },
      {
        "at": [
          29.11,
          38.24
        ]
      },
      {
        "at": [
          69.25,
          97.86
        ]
      },
      {
        "at": [
          98.34,
          103.68
        ]
      },
      {
        "at": [
          106.65,
          119.98
        ]
      }
    ],
    "overlap": [
      {
        "at": [
          37.05,
          37.68
        ],
        "speakers": [
          "SPEAKER_00",
          "SPEAKER_03"
        ]
      },
      {
        "at": [
          37.86,
          38.22
        ],
        "speakers": [
          "SPEAKER_02",
          "SPEAKER_03"
        ]
      },
      {
        "at": [
          69.25,
          70.15
        ],
        "speakers": [
          "SPEAKER_00",
          "SPEAKER_03"
        ]
      }
    ],
    "transcript": "The video features a discussion about notable trends observed in the Winter 2024 startup batch, highlighting that nearly 70% of the ideas involve AI and machine learning. A key shift identified is the resurgence of consumer-focused startups, with founders increasingly pivoting towards consumer ideas rather than traditional enterprise B2B SaaS models. The speakers debate the implications of this trend, with differing opinions on whether pivoting to consumer ideas reflects strategic adaptation or a less rigorous approach.",
    "listen_provider": "tinycloud"
  },
  "meta": {
    "time": "2026-07-13T03:25:08.535Z",
    "provider": "local:pyannote",
    "case": "case:wiretap"
  },
  "media": {
    "ref": "case:wiretap/.overcast/media/separate/interview-tape_SPEAKER_03.wav"
  }
}

{
  "payload": {
    "output": "case:wiretap/.overcast/media/interview-tape_SPEAKER_03_degraded_voiceiso.mp3",
    "ops": [
      "voice-isolation"
    ],
    "provider": "elevenlabs"
  },
  "meta": {
    "time": "2026-07-13T03:29:50.081Z",
    "provider": "elevenlabs:voice-isolator",
    "case": "case:wiretap"
  },
  "media": {
    "ref": "case:wiretap/.overcast/media/interview-tape_SPEAKER_03_degraded_voiceiso.mp3"
  }
}

{
  "payload": {
    "index": "local_voice_print_2a33c2ee",
    "file": "showcase/wiretap/.overcast/media/interview-tape_SPEAKER_03_degraded_voiceiso.mp3",
    "model": "pyannote/wespeaker-voxceleb-resnet34-LM",
    "vectors": 22,
    "speech_seconds": 50.04,
    "window": 3,
    "summary": "enrolled interview-tape_SPEAKER_03_degraded_voiceiso.mp3 into local_voice_print_2a33c2ee (22 voice windows, 50.0s speech)",
    "op": "add",
    "caveat": "speaker similarity is not liveness: a cloned/synthetic voice can score high and cross-language or degraded speech scores lower — corroborate before treating a match as identification"
  },
  "meta": {
    "time": "2026-07-13T03:31:20.091Z",
    "provider": "local:voice-print",
    "model": "pyannote/wespeaker-voxceleb-resnet34-LM",
    "case": "case:wiretap"
  },
  "media": {
    "ref": "showcase/wiretap/.overcast/media/interview-tape_SPEAKER_03_degraded_voiceiso.mp3"
  }
}

{
  "payload": {
    "index": "local_voice_print_2a33c2ee",
    "file": "showcase/wiretap/.overcast/media/separate/interview-tape_SPEAKER_02.wav",
    "model": "pyannote/wespeaker-voxceleb-resnet34-LM",
    "vectors": 11,
    "speech_seconds": 22.89,
    "window": 3,
    "summary": "enrolled interview-tape_SPEAKER_02.wav into local_voice_print_2a33c2ee (11 voice windows, 22.9s speech)",
    "op": "add",
    "caveat": "speaker similarity is not liveness: a cloned/synthetic voice can score high and cross-language or degraded speech scores lower — corroborate before treating a match as identification"
  },
  "meta": {
    "time": "2026-07-13T03:31:23.435Z",
    "provider": "local:voice-print",
    "model": "pyannote/wespeaker-voxceleb-resnet34-LM",
    "case": "case:wiretap"
  },
  "media": {
    "ref": "showcase/wiretap/.overcast/media/separate/interview-tape_SPEAKER_02.wav"
  }
}

{
  "payload": {
    "index": "local_voice_print_2a33c2ee",
    "file": "showcase/wiretap/.overcast/media/separate/interview-tape_SPEAKER_01.wav",
    "model": "pyannote/wespeaker-voxceleb-resnet34-LM",
    "vectors": 6,
    "speech_seconds": 13.95,
    "window": 3,
    "summary": "enrolled interview-tape_SPEAKER_01.wav into local_voice_print_2a33c2ee (6 voice windows, 13.9s speech)",
    "op": "add",
    "caveat": "speaker similarity is not liveness: a cloned/synthetic voice can score high and cross-language or degraded speech scores lower — corroborate before treating a match as identification"
  },
  "meta": {
    "time": "2026-07-13T03:31:26.853Z",
    "provider": "local:voice-print",
    "model": "pyannote/wespeaker-voxceleb-resnet34-LM",
    "case": "case:wiretap"
  },
  "media": {
    "ref": "showcase/wiretap/.overcast/media/separate/interview-tape_SPEAKER_01.wav"
  }
}

{
  "payload": {
    "mode": "windowed",
    "reference": "showcase/wiretap/.overcast/media/interview-tape_SPEAKER_03_degraded_voiceiso.mp3",
    "model": "pyannote/wespeaker-voxceleb-resnet34-LM",
    "windows": 159,
    "skipped_windows": 0,
    "reference_speech_seconds": 50.04,
    "params": {
      "window": 3,
      "step": 0.75,
      "start": null,
      "end": null
    },
    "matches": [
      {
        "file": "showcase/_media/wiretap/interview-tape.wav",
        "at": 15.75,
        "duration": 3,
        "similarity": 100,
        "cosine": 0.7516
      },
      {
        "file": "showcase/_media/wiretap/interview-tape.wav",
        "at": 16.5,
        "duration": 3,
        "similarity": 100,
        "cosine": 0.7932
      },
      {
        "file": "showcase/_media/wiretap/interview-tape.wav",
        "at": 17.25,
        "duration": 3,
        "similarity": 100,
        "cosine": 0.7532
      },
      {
        "file": "showcase/_media/wiretap/interview-tape.wav",
        "at": 18,
        "duration": 3,
        "similarity": 100,
        "cosine": 0.7532
      },
      {
        "file": "showcase/_media/wiretap/interview-tape.wav",
        "at": 18.75,
        "duration": 3,
        "similarity": 100,
        "cosine": 0.7532
      },
      {
        "file": "showcase/_media/wiretap/interview-tape.wav",
        "at": 30.75,
        "duration": 3,
        "similarity": 100,
        "cosine": 0.755
      },
      {
        "file": "showcase/_media/wiretap/interview-tape.wav",
        "at": 31.5,
        "duration": 3,
        "similarity": 100,
        "cosine": 0.7553
      },
      {
        "file": "showcase/_media/wiretap/interview-tape.wav",
        "at": 32.25,
        "duration": 3,
        "similarity": 100,
        "cosine": 0.7705
      },
      {
        "file": "showcase/_media/wiretap/interview-tape.wav",
        "at": 75,
        "duration": 3,
        "similarity": 100,
        "cosine": 0.7602
      },
      {
        "file": "showcase/_media/wiretap/interview-tape.wav",
        "at": 76.5,
        "duration": 3,
        "similarity": 100,
        "cosine": 0.7644
      },
      {
        "file": "showcase/_media/wiretap/interview-tape.wav",
        "at": 78.75,
        "duration": 3,
        "similarity": 100,
        "cosine": 0.7736
      },
      {
        "file": "showcase/_media/wiretap/interview-tape.wav",
        "at": 89.25,
        "duration": 3,
        "similarity": 100,
        "cosine": 0.7845
      },
      {
        "file": "showcase/_media/wiretap/interview-tape.wav",
        "at": 91.5,
        "duration": 3,
        "similarity": 100,
        "cosine": 0.7536
      },
      {
        "file": "showcase/_media/wiretap/interview-tape.wav",
        "at": 93,
        "duration": 3,
        "similarity": 100,
        "cosine": 0.7671
      },
      {
        "file": "showcase/_media/wiretap/interview-tape.wav",
        "at": 97.5,
        "duration": 3,
        "similarity": 100,
        "cosine": 0.7535
      },
      {
        "file": "showcase/_media/wiretap/interview-tape.wav",
        "at": 98.25,
        "duration": 3,
        "similarity": 100,
        "cosine": 0.7692
      },
      {
        "file": "showcase/_media/wiretap/interview-tape.wav",
        "at": 99,
        "duration": 3,
        "similarity": 100,
        "cosine": 0.7512
      },
      {
        "file": "showcase/_media/wiretap/interview-tape.wav",
        "at": 99.75,
        "duration": 3,
        "similarity": 100,
        "cosine": 0.7508
      },
      {
        "file": "showcase/_media/wiretap/interview-tape.wav",
        "at": 100.5,
        "duration": 3,
        "similarity": 100,
        "cosine": 0.7643
      },
      {
        "file": "showcase/_media/wiretap/interview-tape.wav",
        "at": 101.25,
        "duration": 3,
        "similarity": 100,
        "cosine": 0.7565
      }
    ],
    "count": 20,
    "margin": 30.02,
    "summary": "best voice match 100.0 at 15.8s (20 windows >= floor)",
    "op": "match",
    "caveat": "speaker similarity is not liveness: a cloned/synthetic voice can score high and cross-language or degraded speech scores lower — corroborate before treating a match as identification"
  },
  "meta": {
    "time": "2026-07-13T03:31:53.170Z",
    "provider": "local:voice-print",
    "model": "pyannote/wespeaker-voxceleb-resnet34-LM",
    "case": "case:wiretap"
  },
  "media": {
    "ref": "showcase/_media/wiretap/interview-tape.wav",
    "at": 15.75
  }
}

{
  "payload": {
    "text": "Reference voice interview-tape_SPEAKER_03_degraded_voiceiso.mp3 matched at 100.0 similarity in interview-tape.wav — corroborate (a cloned/synthetic voice can score high)",
    "target": "",
    "source_record": "rec_7a7e04a947870fde",
    "source_verb": "voice",
    "trigger": "signal:voice-match",
    "status": "suggested",
    "confidence": "high",
    "signal": {
      "kind": "voice-match",
      "score": 100,
      "threshold": 80,
      "unit": "percent",
      "at": 15.75,
      "matched": "showcase/wiretap/.overcast/media/interview-tape_SPEAKER_03_degraded_voiceiso.mp3"
    }
  },
  "meta": {
    "time": "2026-07-13T03:31:53.171Z",
    "case": "case:wiretap",
    "provider": "automation"
  },
  "media": {
    "ref": "showcase/_media/wiretap/interview-tape.wav",
    "at": 15.75
  }
}

{
  "payload": {
    "mode": "windowed",
    "reference": "showcase/wiretap/.overcast/media/interview-tape_SPEAKER_03_degraded_voiceiso.mp3",
    "model": "pyannote/wespeaker-voxceleb-resnet34-LM",
    "windows": 41,
    "skipped_windows": 118,
    "reference_speech_seconds": 50.04,
    "params": {
      "window": 3,
      "step": 0.75,
      "start": null,
      "end": null
    },
    "matches": [
      {
        "file": "showcase/wiretap/.overcast/media/separate/interview-tape_SPEAKER_02.wav",
        "at": 51,
        "duration": 3,
        "similarity": 58.39,
        "cosine": 0.3234
      },
      {
        "file": "showcase/wiretap/.overcast/media/separate/interview-tape_SPEAKER_02.wav",
        "at": 51.75,
        "duration": 3,
        "similarity": 57.47,
        "cosine": 0.3153
      },
      {
        "file": "showcase/wiretap/.overcast/media/separate/interview-tape_SPEAKER_02.wav",
        "at": 53.25,
        "duration": 3,
        "similarity": 56.76,
        "cosine": 0.3092
      },
      {
        "file": "showcase/wiretap/.overcast/media/separate/interview-tape_SPEAKER_02.wav",
        "at": 54,
        "duration": 3,
        "similarity": 54.21,
        "cosine": 0.2868
      },
      {
        "file": "showcase/wiretap/.overcast/media/separate/interview-tape_SPEAKER_02.wav",
        "at": 52.5,
        "duration": 3,
        "similarity": 53.15,
        "cosine": 0.2775
      },
      {
        "file": "showcase/wiretap/.overcast/media/separate/interview-tape_SPEAKER_02.wav",
        "at": 48,
        "duration": 3,
        "similarity": 52.32,
        "cosine": 0.2703
      },
      {
        "file": "showcase/wiretap/.overcast/media/separate/interview-tape_SPEAKER_02.wav",
        "at": 50.25,
        "duration": 3,
        "similarity": 51.8,
        "cosine": 0.2657
      },
      {
        "file": "showcase/wiretap/.overcast/media/separate/interview-tape_SPEAKER_02.wav",
        "at": 49.5,
        "duration": 3,
        "similarity": 51.5,
        "cosine": 0.2631
      },
      {
        "file": "showcase/wiretap/.overcast/media/separate/interview-tape_SPEAKER_02.wav",
        "at": 48.75,
        "duration": 3,
        "similarity": 51.28,
        "cosine": 0.2612
      }
    ],
    "count": 9,
    "margin": 13.56,
    "summary": "best voice match 58.4 at 51.0s (9 windows >= floor)",
    "op": "match",
    "caveat": "speaker similarity is not liveness: a cloned/synthetic voice can score high and cross-language or degraded speech scores lower — corroborate before treating a match as identification"
  },
  "meta": {
    "time": "2026-07-13T03:31:57.693Z",
    "provider": "local:voice-print",
    "model": "pyannote/wespeaker-voxceleb-resnet34-LM",
    "case": "case:wiretap"
  },
  "media": {
    "ref": "showcase/wiretap/.overcast/media/separate/interview-tape_SPEAKER_02.wav",
    "at": 51
  }
}

{
  "payload": {
    "index": "local_voice_print_2a33c2ee",
    "reference": "showcase/wiretap/.overcast/media/separate/interview-tape_SPEAKER_03.wav",
    "model": "pyannote/wespeaker-voxceleb-resnet34-LM",
    "matches": [
      {
        "ref": "showcase/wiretap/.overcast/media/interview-tape_SPEAKER_03_degraded_voiceiso.mp3",
        "similarity": 100,
        "cosine": 0.7788,
        "duration": 3,
        "windows_over_floor": 22,
        "margin": 6.39,
        "at": 96
      },
      {
        "ref": "showcase/wiretap/.overcast/media/separate/interview-tape_SPEAKER_02.wav",
        "similarity": 61.44,
        "cosine": 0.3501,
        "duration": 3,
        "windows_over_floor": 4,
        "margin": 12.01,
        "at": 51
      }
    ],
    "count": 2,
    "reference_speech_seconds": 50.91,
    "summary": "2 members matched the reference voice",
    "op": "search",
    "caveat": "speaker similarity is not liveness: a cloned/synthetic voice can score high and cross-language or degraded speech scores lower — corroborate before treating a match as identification"
  },
  "meta": {
    "time": "2026-07-13T03:32:01.795Z",
    "provider": "local:voice-print",
    "model": "pyannote/wespeaker-voxceleb-resnet34-LM",
    "case": "case:wiretap"
  },
  "media": {
    "ref": "showcase/wiretap/.overcast/media/separate/interview-tape_SPEAKER_03.wav"
  }
}

{
  "payload": {
    "text": "Four speakers on the tape: pyannote separation of the 2-min Lightcone panel excerpt yields 4 clean tracks (dominant Speaker A 64.0s, plus 30.3s / 18.0s / 5.9s) with only 4 cross-talk regions — clean turn-taking, one track per voice",
    "target": "voice-on-the-tape",
    "source_record": "rec_285619d83592acbd",
    "source_verb": "enhance",
    "trigger": "human",
    "status": "open",
    "target_id": "tgt_982bbd",
    "confidence": "high",
    "ref": "showcase/_media/wiretap/interview-tape.wav"
  },
  "meta": {
    "time": "2026-07-13T03:32:34.027Z",
    "case": "case:wiretap",
    "provider": "human"
  },
  "media": {
    "ref": "showcase/_media/wiretap/interview-tape.wav"
  }
}

{
  "payload": {
    "text": "Audio cleanup recovers a degraded intercept: Speaker A's track was degraded into a telephone-band + hiss 'intercept', then ElevenLabs voice-isolation dropped the noise floor from a full-spectrum haze to a black floor (see gallery before/after). The cleaned track still re-identifies as Speaker A at 100/100 — the cleanup preserved voice identity",
    "target": "voice-on-the-tape",
    "source_record": "rec_832fe00cc90180f8",
    "source_verb": "enhance",
    "trigger": "human",
    "status": "open",
    "target_id": "tgt_982bbd",
    "confidence": "high",
    "ref": "case:wiretap/.overcast/media/interview-tape_SPEAKER_03_degraded_voiceiso.mp3"
  },
  "meta": {
    "time": "2026-07-13T03:32:34.370Z",
    "case": "case:wiretap",
    "provider": "human"
  },
  "media": {
    "ref": "case:wiretap/.overcast/media/interview-tape_SPEAKER_03_degraded_voiceiso.mp3"
  }
}

{
  "payload": {
    "text": "Voice print discriminates: probing the cleaned Speaker A reference finds A on the tape at 100/100 (margin 30) but a different panelist (Speaker B) scores only 58/100 (cosine 0.32) — a clean positive-vs-negative on the same recording. NOT liveness: a cloned voice can score high, corroborate before naming",
    "target": "voice-on-the-tape",
    "source_record": "rec_ce8cb48b8dba9670",
    "source_verb": "voice",
    "trigger": "human",
    "status": "open",
    "target_id": "tgt_982bbd",
    "confidence": "high",
    "ref": "showcase/wiretap/.overcast/media/separate/interview-tape_SPEAKER_02.wav"
  },
  "meta": {
    "time": "2026-07-13T03:32:34.716Z",
    "case": "case:wiretap",
    "provider": "human"
  },
  "media": {
    "ref": "showcase/wiretap/.overcast/media/separate/interview-tape_SPEAKER_02.wav",
    "at": 51
  }
}

{
  "payload": {
    "text": "Voice lineup: probing raw Speaker A against the enrolled panel (cleaned A + Speaker B + Speaker C) picks the Speaker A member at 100/100 vs next-best 61 — the print isolates one voice from the panel. Scores are 0-100 rank scores, NOT liveness; a cloned/synthetic voice can score high, so this is a corroborated lead, not a named identification.",
    "tags": [
      "thread:tgt_982bbd"
    ],
    "confidence": "high",
    "ref": "showcase/wiretap/.overcast/media/separate/interview-tape_SPEAKER_03.wav",
    "related_record": "rec_89d0739709ad93a0"
  },
  "meta": {
    "time": "2026-07-13T03:32:47.208Z",
    "provider": "human",
    "case": "case:wiretap"
  },
  "media": {
    "ref": "showcase/wiretap/.overcast/media/separate/interview-tape_SPEAKER_03.wav"
  }
}

{
  "payload": {
    "text": "Four speakers cleanly separated from a 2-min Lightcone (Y Combinator) panel excerpt. One speaker track was degraded into a telephone-band+hiss 'intercept' and then cleaned with ElevenLabs voice isolation (noise floor haze -> black). The cleaned track re-identifies as Speaker A at 100/100 while a different panelist scores 58/100 - the voice print discriminates. Not liveness; the degradation is a labeled demonstration on a real speaker.",
    "tags": [
      "tldr"
    ]
  },
  "meta": {
    "time": "2026-07-13T03:32:47.851Z",
    "provider": "human",
    "case": "case:wiretap"
  },
  "media": null
}