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编写于
1月 24, 2022
作者:
小湉湉
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1月 24, 2022
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@@ -236,7 +236,7 @@ PaddleSpeech supports a series of most popular models. They are summarized in [r
</thead>
<tbody>
<tr>
<td
rowspan=
"
3
"
>
Speech Recogination
</td>
<td
rowspan=
"
4
"
>
Speech Recogination
</td>
<td
rowspan=
"2"
>
Aishell
</td>
<td
>
DeepSpeech2 RNN + Conv based Models
</td>
<td>
...
...
@@ -249,7 +249,7 @@ PaddleSpeech supports a series of most popular models. They are summarized in [r
<a
href =
"./examples/aishell/asr1"
>
u2.transformer.conformer-aishell
</a>
</td>
</tr>
<tr>
<tr>
<td>
Librispeech
</td>
<td>
Transformer based Attention Models
</td>
<td>
...
...
@@ -257,6 +257,13 @@ PaddleSpeech supports a series of most popular models. They are summarized in [r
</td>
</td>
</tr>
<tr>
<td>
TIMIT
</td>
<td>
Unified Streaming & Non-streaming Two-pass
</td>
<td>
<a
href =
"./examples/timit/asr1"
>
u2-timit
</a>
</td>
</tr>
<tr>
<td>
Alignment
</td>
<td>
THCHS30
</td>
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...
@@ -266,20 +273,13 @@ PaddleSpeech supports a series of most popular models. They are summarized in [r
</td>
</tr>
<tr>
<td
rowspan=
"
2
"
>
Language Model
</td>
<td
rowspan=
"
1
"
>
Language Model
</td>
<td
colspan =
"2"
>
Ngram Language Model
</td>
<td>
<a
href =
"./examples/other/ngram_lm"
>
kenlm
</a>
</td>
</tr>
<tr>
<td>
TIMIT
</td>
<td>
Unified Streaming & Non-streaming Two-pass
</td>
<td>
<a
href =
"./examples/timit/asr1"
>
u2-timit
</a>
</td>
</tr>
<tr>
<tr>
<td
rowspan=
"2"
>
Speech Translation (English to Chinese)
</td>
<td
rowspan=
"2"
>
TED En-Zh
</td>
<td>
Transformer + ASR MTL
</td>
...
...
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