o 9wi*@sdZddlmZddlmZmZmZmZddlZ ddl m Z m Z m Z ddlmZddlmZddlmZdd lmZdd lmZdd lmZdd lmZmZdd lmZde de fddZGdddeZ GdddeZ!dS)z%Overlapped speech detection pipelines)partial)CallableOptionalTextUnionN) AnnotationSlidingWindowFeatureTimeline) get_annotated) DetectionPrecisionRecallFMeasure)Uniform) Inference) AudioFile)Pipeline) PipelineModel get_model)Binarize annotationreturncCsjt|jd}||D] \\}}\}}|||f}|||f}||kr$q |||@q |jdddS)zGet overlapped speech regions Parameters ---------- annotation : Annotation Speaker annotation. Returns ------- overlap : Annotation Overlapped speech annotation. )uristringoverlap) generatormodality)r rco_iteraddsupport to_annotation)rrs1t1s2t2l1l2r$q/home/ubuntu/sommelier/.venv/lib/python3.10/site-packages/pyannote/audio/pipelines/overlapped_speech_detection.py to_overlap)s   r&c@s"eZdZdZdedefddZdS)OracleOverlappedSpeechDetectionz+Oracle overlapped speech detection pipelinefilercCs t|dS)a Return groundtruth overlapped speech detection Parameter --------- file : AudioFile Must provide a "annotation" key. Returns ------- hypothesis : Annotation Overlapped speech regions. r)r&)selfr(r$r$r%applyDs z%OracleOverlappedSpeechDetection.applyN)__name__ __module__ __qualname____doc__rrr*r$r$r$r%r'Asr'c seZdZdZ    ddedeedeedeedfffdd Z d d Z d d Z ddZ dZ ddedeedefddZdefddZdededefddZddZZS)OverlappedSpeechDetectionaOverlapped speech detection pipeline Parameters ---------- segmentation : Model, str, or dict, optional Pretrained segmentation (or overlapped speech detection) model. Defaults to "pyannote/segmentation". See pyannote.audio.pipelines.utils.get_model for supported format. precision : float, optional Optimize recall at target precision. Defaults to optimize precision/recall fscore. recall : float, optional Optimize precision at target recall Defaults to optimize precision/recall fscore use_auth_token : str, optional When loading private huggingface.co models, set `use_auth_token` to True or to a string containing your hugginface.co authentication token that can be obtained by running `huggingface-cli login` inference_kwargs : dict, optional Keywords arguments passed to Inference. Hyper-parameters ---------------- onset, offset : float Onset/offset detection thresholds min_duration_on : float Remove speech regions shorter than that many seconds. min_duration_off : float Fill non-speech regions shorter than that many seconds. pyannote/segmentationN segmentation precisionrecalluse_auth_tokenc st||_t||d}|jdkrdd|d<t|fi||_|jjr-d|_ |_ n t dd|_ t dd|_ t dd|_ t dd|_ |durQ|durQtd ||_||_dS) N)r4cSs&tj|ddddddddtjfS)N)axis)np partitionnewaxis)scoresr$r$r%s z4OverlappedSpeechDetection.__init__..pre_aggregation_hookg?g?zIOne must choose between optimizing for target precision or target recall.)super__init__r1r dimensionr _segmentationspecificationspowersetonsetoffsetr min_duration_onmin_duration_off ValueErrorr2r3)r)r1r2r3r4inference_kwargsmodel __class__r$r%rAts$         z"OverlappedSpeechDetection.__init__cCs2|jdkr dddddS|jdkrddd St) Nr0gQ?g{Gz?gK?g;On?rFrGrHrIzpyannote/segmentation-3.0.0r?)rHrI)r1NotImplementedErrorr)r$r$r%default_parameterss  z,OverlappedSpeechDetection.default_parameterscCsdgS)NOVERLAPr$rQr$r$r%classessz!OverlappedSpeechDetection.classescCst|j|j|j|jd|_dS)z2Initialize pipeline with current set of parametersrON)rrFrGrHrI _binarizerQr$r$r% initializes  z$OverlappedSpeechDetection.initializezcache/segmentation/inferencer(hookrcCs|j||d}|jr&|j|vr||j}n|j|t|ddd}|||j<n |j|t|ddd}|d|||}|d|_|dd|DS)aApply overlapped speech detection Parameters ---------- file : AudioFile Processed file. hook : callable, optional Callback called after each major steps of the pipeline as follows: hook(step_name, # human-readable name of current step step_artefact, # artifact generated by current step file=file) # file being processed Time-consuming steps call `hook` multiple times with the same `step_name` and additional `completed` and `total` keyword arguments usable to track progress of current step. Returns ------- overlapped_speech : Annotation Overlapped speech regions. )rWr1NrcSsi|]}|dqS)rSr$).0labelr$r$r% sz3OverlappedSpeechDetection.apply..) setup_hooktrainingCACHED_SEGMENTATIONrCrrUr rename_labelslabels)r)r(rW segmentationsoverlapped_speechr$r$r%r*s"        zOverlappedSpeechDetection.applycKs2|jdus |jdurtdGdddt}|S)zGet overlapped speech detection metric Returns ------- metric : DetectionPrecisionRecallFMeasure Detection metric. Nz4pyannote.pipeline should use `loss` method fallback.c s6eZdZ ddededeedeffdd ZZS) z5OverlappedSpeechDetection.get_metric.._MetricN reference hypothesisuemrcstjt||fd|i|S)Nrd)r@compute_componentsr&)_selfrbrcrdkwargsrMr$r%reszHOverlappedSpeechDetection.get_metric.._Metric.compute_componentsN) r+r,r-rrr dictre __classcell__r$r$rMr%_Metricsrk)r2r3rPr )r)rgrkr$r$r% get_metrics   z$OverlappedSpeechDetection.get_metricrcc Cst}d|vr |d}n |d}t|}||d<|||t|d}|\}}}|jdur9||jkr7||jS|S|jdurJ||jkrH||jS|SdS)aCompute recall at target precision (or vice versa) Parameters ---------- file : AudioFile Processed file. hypothesis : Annotation Hypothesized overlapped speech regions. Returns ------- recall (or purity) : float When optimizing for target precision: If precision < target_precision, returns (precision - target_precision). If precision > target_precision, returns recall. When optimizing for target recall: If recall < target_recall, returns (recall - target_recall). If recall > target_recall, returns precision. overlap_referencer)rdN)r r&r compute_metricsr2r3) r)r(rcfmeasurermrb_r2r3r$r$r%loss s"       zOverlappedSpeechDetection.losscCsdS)Nmaximizer$rQr$r$r% get_direction9sz'OverlappedSpeechDetection.get_direction)r0NNNrh)r+r,r-r.rrfloatrrrArRrTrVr]rrrr*r rlrqrsrjr$r$rMr%r/Ts.! * 0.r/)"r. functoolsrtypingrrrrnumpyr9 pyannote.corerrr pyannote.databaser pyannote.metrics.detectionr pyannote.pipeline.parameterr pyannote.audior pyannote.audio.core.iorpyannote.audio.core.pipelinerpyannote.audio.pipelines.utilsrrpyannote.audio.utils.signalrr&r'r/r$r$r$r%s