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Update README.md (#2146)

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@ -95,7 +95,9 @@ Recommendations:
When you input long audio and encounter Out Of Memory (OOM) issues, since memory usage tends to increase quadratically with audio length, consider the following three scenarios: When you input long audio and encounter Out Of Memory (OOM) issues, since memory usage tends to increase quadratically with audio length, consider the following three scenarios:
a) At the beginning of inference, memory usage primarily depends on `batch_size_s`. Appropriately reducing this value can decrease memory usage. a) At the beginning of inference, memory usage primarily depends on `batch_size_s`. Appropriately reducing this value can decrease memory usage.
b) During the middle of inference, when encountering long audio segments cut by VAD and the total token count is less than `batch_size_s`, yet still facing OOM, you can appropriately reduce `batch_size_threshold_s`. If the threshold is exceeded, the batch size is forced to 1. b) During the middle of inference, when encountering long audio segments cut by VAD and the total token count is less than `batch_size_s`, yet still facing OOM, you can appropriately reduce `batch_size_threshold_s`. If the threshold is exceeded, the batch size is forced to 1.
c) Towards the end of inference, if long audio segments cut by VAD have a total token count less than `batch_size_s` and exceed the `threshold` batch_size_threshold_s, forcing the batch size to 1 and still facing OOM, you may reduce `max_single_segment_time` to shorten the VAD audio segment length. c) Towards the end of inference, if long audio segments cut by VAD have a total token count less than `batch_size_s` and exceed the `threshold` batch_size_threshold_s, forcing the batch size to 1 and still facing OOM, you may reduce `max_single_segment_time` to shorten the VAD audio segment length.
#### Speech Recognition (Streaming) #### Speech Recognition (Streaming)
@ -421,4 +423,4 @@ result = model(wav_path)
print(result) print(result)
``` ```
More examples ref to [demo](https://github.com/alibaba-damo-academy/FunASR/tree/main/runtime/python/onnxruntime) More examples ref to [demo](https://github.com/alibaba-damo-academy/FunASR/tree/main/runtime/python/onnxruntime)