Referensi:
mikrofon-tunggal
Gunakan perintah berikut untuk memuat kumpulan data ini di TFDS:
ds = tfds.load('huggingface:ami/microphone-single')
- Keterangan :
The AMI Meeting Corpus consists of 100 hours of meeting recordings. The recordings use a range of signals
synchronized to a common timeline. These include close-talking and far-field microphones, individual and
room-view video cameras, and output from a slide projector and an electronic whiteboard. During the meetings,
the participants also have unsynchronized pens available to them that record what is written. The meetings
were recorded in English using three different rooms with different acoustic properties, and include mostly
non-native speakers.
Far field audio of single microphone. This configuration only includes audio belonging the first microphone, *i.e.* 1-1, of the microphone array.
- Lisensi : Tidak ada lisensi yang diketahui
- Versi : 1.6.2
- Perpecahan :
| Membelah | Contoh |
|---|---|
'test' | 16 |
'train' | 134 |
'validation' | 18 |
- Fitur :
{
"word_ids": {
"feature": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"length": -1,
"id": null,
"_type": "Sequence"
},
"word_start_times": {
"feature": {
"dtype": "float32",
"id": null,
"_type": "Value"
},
"length": -1,
"id": null,
"_type": "Sequence"
},
"word_end_times": {
"feature": {
"dtype": "float32",
"id": null,
"_type": "Value"
},
"length": -1,
"id": null,
"_type": "Sequence"
},
"word_speakers": {
"feature": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"length": -1,
"id": null,
"_type": "Sequence"
},
"segment_ids": {
"feature": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"length": -1,
"id": null,
"_type": "Sequence"
},
"segment_start_times": {
"feature": {
"dtype": "float32",
"id": null,
"_type": "Value"
},
"length": -1,
"id": null,
"_type": "Sequence"
},
"segment_end_times": {
"feature": {
"dtype": "float32",
"id": null,
"_type": "Value"
},
"length": -1,
"id": null,
"_type": "Sequence"
},
"segment_speakers": {
"feature": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"length": -1,
"id": null,
"_type": "Sequence"
},
"words": {
"feature": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"length": -1,
"id": null,
"_type": "Sequence"
},
"channels": {
"feature": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"length": -1,
"id": null,
"_type": "Sequence"
},
"file": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"audio": {
"sampling_rate": 16000,
"mono": true,
"decode": true,
"id": null,
"_type": "Audio"
}
}
mikrofon-multi
Gunakan perintah berikut untuk memuat kumpulan data ini di TFDS:
ds = tfds.load('huggingface:ami/microphone-multi')
- Keterangan :
The AMI Meeting Corpus consists of 100 hours of meeting recordings. The recordings use a range of signals
synchronized to a common timeline. These include close-talking and far-field microphones, individual and
room-view video cameras, and output from a slide projector and an electronic whiteboard. During the meetings,
the participants also have unsynchronized pens available to them that record what is written. The meetings
were recorded in English using three different rooms with different acoustic properties, and include mostly
non-native speakers.
Far field audio of microphone array. This configuration includes audio of the first microphone array 1-1, 1-2, ..., 1-8.
- Lisensi : Tidak ada lisensi yang diketahui
- Versi : 1.6.2
- Perpecahan :
| Membelah | Contoh |
|---|---|
'test' | 16 |
'train' | 134 |
'validation' | 18 |
- Fitur :
{
"word_ids": {
"feature": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"length": -1,
"id": null,
"_type": "Sequence"
},
"word_start_times": {
"feature": {
"dtype": "float32",
"id": null,
"_type": "Value"
},
"length": -1,
"id": null,
"_type": "Sequence"
},
"word_end_times": {
"feature": {
"dtype": "float32",
"id": null,
"_type": "Value"
},
"length": -1,
"id": null,
"_type": "Sequence"
},
"word_speakers": {
"feature": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"length": -1,
"id": null,
"_type": "Sequence"
},
"segment_ids": {
"feature": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"length": -1,
"id": null,
"_type": "Sequence"
},
"segment_start_times": {
"feature": {
"dtype": "float32",
"id": null,
"_type": "Value"
},
"length": -1,
"id": null,
"_type": "Sequence"
},
"segment_end_times": {
"feature": {
"dtype": "float32",
"id": null,
"_type": "Value"
},
"length": -1,
"id": null,
"_type": "Sequence"
},
"segment_speakers": {
"feature": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"length": -1,
"id": null,
"_type": "Sequence"
},
"words": {
"feature": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"length": -1,
"id": null,
"_type": "Sequence"
},
"channels": {
"feature": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"length": -1,
"id": null,
"_type": "Sequence"
},
"file-1-1": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"file-1-2": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"file-1-3": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"file-1-4": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"file-1-5": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"file-1-6": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"file-1-7": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"file-1-8": {
"dtype": "string",
"id": null,
"_type": "Value"
}
}
headset-tunggal
Gunakan perintah berikut untuk memuat kumpulan data ini di TFDS:
ds = tfds.load('huggingface:ami/headset-single')
- Keterangan :
The AMI Meeting Corpus consists of 100 hours of meeting recordings. The recordings use a range of signals
synchronized to a common timeline. These include close-talking and far-field microphones, individual and
room-view video cameras, and output from a slide projector and an electronic whiteboard. During the meetings,
the participants also have unsynchronized pens available to them that record what is written. The meetings
were recorded in English using three different rooms with different acoustic properties, and include mostly
non-native speakers.
Close talking audio of single headset. This configuration only includes audio belonging to the headset of the person currently speaking.
- Lisensi : Tidak ada lisensi yang diketahui
- Versi : 1.6.2
- Perpecahan :
| Membelah | Contoh |
|---|---|
'test' | 16 |
'train' | 136 |
'validation' | 18 |
- Fitur :
{
"word_ids": {
"feature": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"length": -1,
"id": null,
"_type": "Sequence"
},
"word_start_times": {
"feature": {
"dtype": "float32",
"id": null,
"_type": "Value"
},
"length": -1,
"id": null,
"_type": "Sequence"
},
"word_end_times": {
"feature": {
"dtype": "float32",
"id": null,
"_type": "Value"
},
"length": -1,
"id": null,
"_type": "Sequence"
},
"word_speakers": {
"feature": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"length": -1,
"id": null,
"_type": "Sequence"
},
"segment_ids": {
"feature": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"length": -1,
"id": null,
"_type": "Sequence"
},
"segment_start_times": {
"feature": {
"dtype": "float32",
"id": null,
"_type": "Value"
},
"length": -1,
"id": null,
"_type": "Sequence"
},
"segment_end_times": {
"feature": {
"dtype": "float32",
"id": null,
"_type": "Value"
},
"length": -1,
"id": null,
"_type": "Sequence"
},
"segment_speakers": {
"feature": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"length": -1,
"id": null,
"_type": "Sequence"
},
"words": {
"feature": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"length": -1,
"id": null,
"_type": "Sequence"
},
"channels": {
"feature": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"length": -1,
"id": null,
"_type": "Sequence"
},
"file": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"audio": {
"sampling_rate": 16000,
"mono": true,
"decode": true,
"id": null,
"_type": "Audio"
}
}
headset-multi
Gunakan perintah berikut untuk memuat kumpulan data ini di TFDS:
ds = tfds.load('huggingface:ami/headset-multi')
- Keterangan :
The AMI Meeting Corpus consists of 100 hours of meeting recordings. The recordings use a range of signals
synchronized to a common timeline. These include close-talking and far-field microphones, individual and
room-view video cameras, and output from a slide projector and an electronic whiteboard. During the meetings,
the participants also have unsynchronized pens available to them that record what is written. The meetings
were recorded in English using three different rooms with different acoustic properties, and include mostly
non-native speakers.
Close talking audio of four individual headset. This configuration includes audio belonging to four individual headsets. For each annotation there are 4 audio files 0, 1, 2, 3.
- Lisensi : Tidak ada lisensi yang diketahui
- Versi : 1.6.2
- Perpecahan :
| Membelah | Contoh |
|---|---|
'test' | 16 |
'train' | 136 |
'validation' | 18 |
- Fitur :
{
"word_ids": {
"feature": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"length": -1,
"id": null,
"_type": "Sequence"
},
"word_start_times": {
"feature": {
"dtype": "float32",
"id": null,
"_type": "Value"
},
"length": -1,
"id": null,
"_type": "Sequence"
},
"word_end_times": {
"feature": {
"dtype": "float32",
"id": null,
"_type": "Value"
},
"length": -1,
"id": null,
"_type": "Sequence"
},
"word_speakers": {
"feature": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"length": -1,
"id": null,
"_type": "Sequence"
},
"segment_ids": {
"feature": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"length": -1,
"id": null,
"_type": "Sequence"
},
"segment_start_times": {
"feature": {
"dtype": "float32",
"id": null,
"_type": "Value"
},
"length": -1,
"id": null,
"_type": "Sequence"
},
"segment_end_times": {
"feature": {
"dtype": "float32",
"id": null,
"_type": "Value"
},
"length": -1,
"id": null,
"_type": "Sequence"
},
"segment_speakers": {
"feature": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"length": -1,
"id": null,
"_type": "Sequence"
},
"words": {
"feature": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"length": -1,
"id": null,
"_type": "Sequence"
},
"channels": {
"feature": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"length": -1,
"id": null,
"_type": "Sequence"
},
"file-0": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"file-1": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"file-2": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"file-3": {
"dtype": "string",
"id": null,
"_type": "Value"
}
}